{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "5b749521",
   "metadata": {},
   "source": [
    "# 基于Darts的股票价格时间序列预测\n",
    "\n",
    "Python的darts包是一个用于时间序列预测和分析的库。它提供了丰富的功能来处理时间序列数据，包括数据预处理、特征提取、模型构建、预测及评估等。Darts特别适用于进行时间序列的深度学习模型构建，如RNNs、LSTMs等，同时也支持传统的统计方法和机器学习模型。此外，它还允许用户方便地比较不同模型性能，以及进行模型的组合以进一步提升预测准确性。总之，darts包是进行时间序列分析和预测任务的一个强大工具。\n",
    "\n",
    "\n",
    "参考资料：\n",
    "\n",
    "\n",
    "https://www.kaggle.com/code/stpeteishii/google-stock-prediction-darts\n",
    "\n",
    "https://github.com/unit8co/darts#forecasting-models\n",
    "\n",
    "https://github.com/unit8co/darts/blob/master/examples/09-DeepTCN-examples.ipynb\n",
    "\n",
    "\n",
    "多变量与单变量\n",
    "\n",
    "https://www.163.com/dy/article/IVNUJI3U0531D9VR.html\n",
    "\n",
    "\n",
    "4大类11种常见的时间序列预测方法\n",
    "\n",
    "https://zhuanlan.zhihu.com/p/472739821"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "bc55a7d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import sqlite3\n",
    "import pandas as pd  \n",
    "# define prediction period\n",
    "from datetime import datetime\n",
    "from datetime import date\n",
    "from datetime import timedelta\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from scipy.stats import pearsonr, spearmanr\n",
    "from darts.dataprocessing.transformers import Scaler\n",
    "from darts import TimeSeries\n",
    "from darts.utils.timeseries_generation import gaussian_timeseries, linear_timeseries, sine_timeseries\n",
    "from darts.models import RNNModel, TCNModel, TransformerModel, NBEATSModel, BlockRNNModel\n",
    "from darts.models import ExponentialSmoothing, TBATS, AutoARIMA, Theta\n",
    "from darts.metrics import mape, smape\n",
    "\n",
    "%matplotlib inline \n",
    "#正常显示画图时出现的中文和负号\n",
    "from pylab import mpl\n",
    "\n",
    "mpl.rcParams['font.sans-serif']=['SimHei']\n",
    "mpl.rcParams['axes.unicode_minus']=False"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9bbf1df0",
   "metadata": {},
   "source": [
    "## darts的时间序列的构建和操作\n",
    "\n",
    "\n",
    "TimeSeries 是 Darts 中的主要数据类。TimeSeries 表示一个具有合适时间索引的单变量或多变量时间序列。时间索引可以是 pandas.DatetimeIndex 类型（包含日期时间），或者是 pandas.RangeIndex 类型（包含整数；对于表示没有特定时间戳的顺序数据很有用）。在某些情况下，TimeSeries 甚至可以表示概率序列，以便例如获得置信区间。Darts 中的所有模型都要求 TimeSeries 并且输出结果也是 TimeSeries。\n",
    "\n",
    "读取数据并构建 TimeSeries\n",
    "TimeSeries 可以使用几个工厂方法轻松构建：\n",
    "\n",
    "对于 Pandas DataFrame，通过 TimeSeries.from_dataframe() 转换。\n",
    "\n",
    "时间索引和对应的值数组，通过 TimeSeries.from_times_and_values() 转换。\n",
    "\n",
    "NumPy 值数组，通过 TimeSeries.from_values() 转换。\n",
    "\n",
    "Pandas Series，通过 TimeSeries.from_series() 转换。\n",
    "\n",
    "xarray.DataArray，通过 TimeSeries.from_xarray() 转换。\n",
    "\n",
    "CSV 文件，使用 TimeSeries.from_csv() 转换。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "75ddf175",
   "metadata": {},
   "outputs": [],
   "source": [
    "conn=sqlite3.connect(r'F:\\BaiduNetdiskDownload\\stock_2018_daily\\stock_2018.db')\n",
    "stock_ml=pd.read_sql(\"select * from stock_daily where 股票代码>'002500.SZ' and 交易日期>'20210217'\",con=conn)\n",
    "stock_ml.columns=['index', 'date', '股票代码', '股票简称', 'open', 'high', 'low', 'close', 'volume',\n",
    "           '成交额(千元)', '换手率(%)', '量比', '市盈率(静态)', '市盈率(TTM)', '市盈率(动态)', '市净率',\n",
    "           '市销率', '市销率(TTM)', '股息率(%)', '股息率(TTM)(%)', '总股本(万股)', '流通股本(万股)',\n",
    "           '总市值(万元)', '流通市值(万元)']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "990de9a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "stork_byd=stock_ml[stock_ml[\"股票代码\"]==\"002594.SZ\"][[\"date\",\"close\"]].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9b60a3b3",
   "metadata": {},
   "outputs": [],
   "source": [
    "stork_byd[\"date\"]=pd.to_datetime(stork_byd[\"date\"].astype(str))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1545c58f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>44189</th>\n",
       "      <td>2021-02-18</td>\n",
       "      <td>264.1698</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44190</th>\n",
       "      <td>2021-02-19</td>\n",
       "      <td>262.4970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44191</th>\n",
       "      <td>2021-02-22</td>\n",
       "      <td>244.3104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44192</th>\n",
       "      <td>2021-02-23</td>\n",
       "      <td>229.5000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44193</th>\n",
       "      <td>2021-02-24</td>\n",
       "      <td>213.1698</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44670</th>\n",
       "      <td>2023-02-13</td>\n",
       "      <td>288.0511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44671</th>\n",
       "      <td>2023-02-14</td>\n",
       "      <td>287.6940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44672</th>\n",
       "      <td>2023-02-15</td>\n",
       "      <td>284.6637</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44673</th>\n",
       "      <td>2023-02-16</td>\n",
       "      <td>282.6435</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44674</th>\n",
       "      <td>2023-02-17</td>\n",
       "      <td>277.1747</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>486 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            date     close\n",
       "44189 2021-02-18  264.1698\n",
       "44190 2021-02-19  262.4970\n",
       "44191 2021-02-22  244.3104\n",
       "44192 2021-02-23  229.5000\n",
       "44193 2021-02-24  213.1698\n",
       "...          ...       ...\n",
       "44670 2023-02-13  288.0511\n",
       "44671 2023-02-14  287.6940\n",
       "44672 2023-02-15  284.6637\n",
       "44673 2023-02-16  282.6435\n",
       "44674 2023-02-17  277.1747\n",
       "\n",
       "[486 rows x 2 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stork_byd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "66a1715b",
   "metadata": {},
   "outputs": [],
   "source": [
    "start0 = datetime.strptime('2021-02-18','%Y-%m-%d').date()\n",
    "end0   = datetime.strptime('2023-02-17','%Y-%m-%d').date()\n",
    "dates0=[]\n",
    "for i in range(1,(end0-start0).days):\n",
    "    dates0+=[(start0+timedelta(i)).strftime('%Y-%m-%d') ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e4aa5fce",
   "metadata": {},
   "outputs": [],
   "source": [
    "data3=pd.DataFrame(columns=['date'],data = dates0)\n",
    "data3['date']=pd.to_datetime(data3['date'])\n",
    "data3=data3.merge(stork_byd,how='left',on='date')\n",
    "data3=data3.ffill()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e08c5942",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'darts.timeseries.TimeSeries'>\n"
     ]
    }
   ],
   "source": [
    "series_stock=TimeSeries.from_dataframe(data3, time_col='date', value_cols='close')\n",
    "print(type(series_stock))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "fe029474",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1cd0dbf4fd0>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scaler_stock = Scaler()\n",
    "stock_scaled = scaler_stock.fit_transform(series_stock)\n",
    "stock_scaled.plot(label='close')\n",
    "plt.legend(loc='best')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "61a41de4",
   "metadata": {},
   "source": [
    "## 基本训练流程"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "83209576",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GPU available: True (cuda), used: True\n",
      "TPU available: False, using: 0 TPU cores\n",
      "IPU available: False, using: 0 IPUs\n",
      "HPU available: False, using: 0 HPUs\n",
      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n",
      "\n",
      "  | Name          | Type             | Params\n",
      "---------------------------------------------------\n",
      "0 | criterion     | MSELoss          | 0     \n",
      "1 | train_metrics | MetricCollection | 0     \n",
      "2 | val_metrics   | MetricCollection | 0     \n",
      "3 | stacks        | ModuleList       | 6.2 M \n",
      "---------------------------------------------------\n",
      "6.2 M     Trainable params\n",
      "1.4 K     Non-trainable params\n",
      "6.2 M     Total params\n",
      "24.787    Total estimated model params size (MB)\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d1230e2539584c58863bdaa0c3723ca2",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Training: |          | 0/? [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "`Trainer.fit` stopped: `max_epochs=50` reached.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "NBEATSModel(output_chunk_shift=0, generic_architecture=True, num_stacks=30, num_blocks=1, num_layers=4, layer_widths=256, expansion_coefficient_dim=5, trend_polynomial_degree=2, dropout=0.0, activation=ReLU, input_chunk_length=24, output_chunk_length=12, n_epochs=50, random_state=0)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_stock, val_stock = stock_scaled[:600], stock_scaled[600:]\n",
    "model = NBEATSModel(input_chunk_length=24, output_chunk_length=12, n_epochs=50, random_state=0)\n",
    "model.fit(train_stock, verbose=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "4585b012",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GPU available: True (cuda), used: True\n",
      "TPU available: False, using: 0 TPU cores\n",
      "IPU available: False, using: 0 IPUs\n",
      "HPU available: False, using: 0 HPUs\n",
      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "17d71e029814461b937ed554825662a5",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Predicting: |          | 0/? [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1f92c2c8c40>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pred = model.predict(n=10, series=train_stock)\n",
    "stock_scaled.plot(label='actual')\n",
    "pred.plot(label='forecast')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "043d2e59",
   "metadata": {},
   "source": [
    "## 模型评价与可视化\n",
    "\n",
    "平均绝对百分比误差（MAPE）darts.metrics包含了更多的指标来比较时间序列。当两个序列未对齐时，这些指标只会比较序列中共有的切片部分\n",
    "\n",
    "**概率预测** 不仅仅提供点预测，还提供可能的未来结果分布。这些输出分布代表了不同未来值发生的可能性，允许在不确定性下进行更加明智的决策。比如说在观测值严格为正的情况下，如销售量或能耗，概率预测可能使用对数正态或伽玛分布来模拟可能结果的范围。概率预测在风险管理和规划中特别有用，因为它使利益相关者能够评估从最悲观到最乐观的各种情景的可能性。\n",
    "\n",
    "在Darts库中，`historical_forecasts`方法主要用于进行回测（backtesting）和评估时间序列预测模型的性能。此方法通过模拟历史预测的方式工作，即在每个时间点上，它使用到那时为止的观测数据来训练或重训模型，然后预测接下来的一段时期（由`forecast_horizon`参数定义）。这个过程沿着时间轴逐步向前推进，从而生成一系列的预测，这些预测可以与实际发生的值进行比较，以评估模型的准确性和稳定性。\n",
    "\n",
    "`historical_forecasts`的主要作用和特点包括：\n",
    "\n",
    "1. **模型验证**：提供了一种无偏见的方法来估计模型在未知数据上的表现，因为每个预测都是基于模型在不包括预测时间段的数据上训练得出的。\n",
    "\n",
    "2. **性能评估**：通过比较预测值和实际值，可以计算各种误差指标（如MAE、MSE、RMSE、MAPE等），进而评估模型的预测精度。\n",
    "\n",
    "3. **参数调优**：根据回测结果，可以调整模型参数以优化预测性能。\n",
    "\n",
    "4. **不确定性估计**：如果模型支持概率预测，`historical_forecasts`还可以用于评估预测的不确定性，比如通过计算预测区间来理解预测的可靠性。\n",
    "\n",
    "5. **模型比较**：通过在相同的历史预测框架下比较不同模型的表现，可以选择最适合特定数据集的模型。\n",
    "\n",
    "使用此方法时，开发者通常需要指定如下关键参数：\n",
    "- **forecast_horizon**：预测的期数，即向前看多少个时间步。\n",
    "- **retrain**：一个布尔值，指示在每个时间步是否重新训练模型。\n",
    "- **start**：开始进行历史预测的起始时间点。\n",
    "- **end**：历史预测结束的时间点（可选）。\n",
    "- **verbose**：是否打印预测过程的详细信息。\n",
    "\n",
    "通过这种方式，`historical_forecasts`为时间序列预测模型的开发和评估提供了一个强大的工具，帮助数据科学家和分析师更好地理解和优化他们的预测模型。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "2224235b",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GPU available: True (cuda), used: True\n",
      "TPU available: False, using: 0 TPU cores\n",
      "IPU available: False, using: 0 IPUs\n",
      "HPU available: False, using: 0 HPUs\n",
      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c288ae7923404cffa3ef3f3ef1db0ef7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Predicting: |          | 0/? [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "model NBEATSModel(input_chunk_length=24, output_chunk_length=12, n_epochs=100, random_state=0) obtains MAPE: 27.75%\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1f9191806a0>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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MDMTt2/IJLdSm6JaGj++//151n2rh4/bt2xAEQZzJkkhLHHBKRKQhaeWjZs2a4u1PP/20alBQnu0iZQwr+fn5JgNRCwoKkJ2d7bR2EzmC4YOISEPGAad6vR7PPvssGjdujObNm5s928BY0cjIyJBdaA4oOlUSKJoXIisry+SxysoKkVbY7UJEpCFp5aNcuXLYv3+/xe2l13yRVj8eeOABhIaGiutqk0Xdvn1bnA2TSEusfBARaUg65sMWJ06cUL19yZIlCA4OtvhYDjolT8HwQUSkIWnlw14PPvggHnroIYSEhFjcbtu2bXY/B5EzMXwQEWlIOubDXsYLk1kLHx988AHy8/Ptfh4iZ2H4ICLSUHErH2+++abJbbaGDwBISUmRrQuCgNGjR6Nv375ITU21qQ1EjmL4ICLSUHHHfHz00UcmtxmvCaMWPlq3bi1b/+uvv8QLiwHApk2bMHXqVCxfvhyvv/66ze0mcgTDBxGRhopb+QgODja53oulykeNGjXQr18/cf2ZZ55BhQoV8McffwAA9u7dK963bNmy4jWeyE4MH0REGrJnzEe5cuVk68YL0qmd7RISEoJq1arJbsvPz8fPP/8M4F5wIXInhg8iIg3Zc7ZL586dZetPPPEEAPXKR0hIiGrASE9PBwCEh4fb9JyCIODrr7/G9OnTYTAYbG4rkRpOMkZEpJFLly6JX+S2jvkAgFatWuHcuXPYuXMnEhISxGnZ7Qkf0knLLNm5cydeeeUVAEWzrA4fPtzm9hIpsfJBRKSRZ5991u7HVq1aFS1btkT16tXF2+wJH8rrvQwePFg1kCxZskRcfuONN+xuNxHA8EFEpJm///5bXL5z547D+zMXPoxjQqTS09NhMBhMwseCBQswc+ZMk+2lIYfIUQwfREQewFiJcIS5AadqlY9///0XVatWxdatW03umz9/vsltynEeubm5DrSU/B3DB5EbHDt2DM8884ysdE0k5Ywrzhan2wUAEhMTsWPHDpPbz5w5Y3JhOuVVcqVzhRAVF8MHkRu0b98eK1asQP/+/ZGZmal1c8gDKbs/7GEufEivdmurhg0bIi8vT1xXhg9nVGrIfzF8ELlBcnKyuOyMX7hEasyFjzJlyhR7X4cOHRInIgNMw4czxqiQ/2L4IHIzW09tJCouc+EjNjYWc+bMQZcuXYq1v0uXLonLysrMc889h/bt2yMpKcm+xpJfY/ggcjOGD3IVc+EDAF555RWsXbu2WJOZXbx4UVxWVj7Onj2LLVu2mEz1TmQLhg8iJ0tLS8OsWbNw4MAB1ftzcnLc3CLyRMoBnc5g7mwXqQULFti8P2nlQxk+jLZs2WLz/oiMGD6InGz48OEYMWIE2rdvLxuwZ8TwQUDR9VWkVq1a5fA+LVU+jF544QUcOXLEbAipU6eOuGyp8iF1/fr1YraU/B3DB5GT/fDDDwCKBpaq9YcfPHgQ7dq1w/jx493cMvIk0nkymjZtiu7duzu8T1vCBwDUrVtXnJJdatiwYVizZg3Kly8PoOgUceP8Hgwf5EwMH0ROpCylq12Aa9iwYdi6dSsmTJiA48ePu6tp5GGk4cP4Ze8otaCh1hUDALGxsbL1MmXK4Msvv0TNmjXRrFkzAEVdiMbXqKXwwQnHqLgYPoic6ObNm7J1tW4XqcTERFc2hzyY9Avbnnk41Nha+QCAWrVqoVq1auJ6+/btxeWWLVuKy3/99RcAhg9yLl7VlsiJzpw5I1u3Fj6c9aVD3kf6hW0uIBSXLQNOjYKCgnDo0CHs3LkTYWFhssARHx8vLl+7dg0Awwc5F8MHkRMdPHhQtm7tQ7mgoMCFrSFP9sknn4jLWlQ+AKBkyZLo1KmTye1hYWHick5ODgoKCmSTisXHx+PkyZPiOsMHFRe7XYicaOfOnbJ1a5UPZ0ypTd5HEAQsXLhQXNcqfJgjDR+5ublITk4Wxy/16NEDJ06cwIwZM2TbEBUHwweRE0kvkQ5YDx887dY/KSea8+TwkZOTgytXrojrFStWBCBvM1/HVFwMH0ROlJqaKltn5YPUuGqWW2eFD2WwkA6MVgsf6enpuHPnjksmTiPfxPBB5ETKiaOslaP5i9E/KV8nytBqr8DAQAQGBspuc0a3i7TyUalSJQDy8PHGG28gKioKTZs2ZRcM2YThg8iJlF8qrHyQGuXrJCUlxWn7lp7xEhAQUKxruRhJw8fKlSuxdOlScV2t8mG0b98+bNq0qdjPR/6H4YPISQoLC03Kznl5eaoTjRkxfPgnZfiIiIhw2r6llQ57T+GVhg8A2L9/v7hsDB/KbYwOHz5s13OSf2H4IHIS5RcKUBQ+Zs6cafYx7HbxT8rXyocffui0fTsjfFgaABsXF2dxmyNHjtj1nORfGD6InMRc+HjrrbfMPoaVD/8kHXDarVs31eus2MsZ4cNcV03ZsmXFfZoLH6x8kC2KFT6WLVuGjh07YvDgwbh9+7bZ7S5duoRnn30W7du3x+jRozkAifyC2hkMapWNxo0bW7yffJ80qJYrV86p+3ZG+DDH2OUCmA8f58+f5+R5ZJXN4ePkyZNYsmQJli9fjr59+2LOnDlmt/3yyy/x1ltvYdOmTQgJCXHKpaKJPJ1a5SM9PV223qVLFyxZskRcnzt3LjIyMlzeNvIs0teKuQu/2Uu6P2eHD+OZLoD58HH37l1cvnzZqc9LvsfmYdA7duxA165dER0djbZt22LevHlmt7148SIefPBBBAQEoH79+khOTja7bX5+vsmHtl6vd/ob0l2MgwstDTL0djxGdWoVvqlTp8rWAwMDTT60v/nmG4wcOVJ226FDh1C+fHmn/yqW8uV/R08/NulrJSgoyK52mjtGZeXDmX+DmjVrivuzFGxOnTqFqlWrOvx8nv7v6Ay+dowBAbbVNGwOHykpKUhISAAA6HQ66PV65OTkqI54rlGjBtauXYuOHTti48aNGDx4sNn9Lly40CTI9O7dG3369LG1aR7JH65WymOUu3jxotVt7t69azKnw++//45evXqJ67/99htee+01REdHY9u2bYiKirK5Dfbw5X9HTz026bwZOTk5uHTpkt37snSMgiA4tG+ptm3bomfPnuL+lKcHh4WFid2Ie/fulV2czlGe+u/oTL5yjNIrJVtic/gwGAyy08FCQ0ORmZmpGj769OmDsWPH4rfffoNer0eTJk3M7nfAgAHo37+/vFFeXvlITExEpUqVbE6A3obHqC4zM9PqNpGRkbj//vtlt9WqVQtVqlQR18eMGQMASEtLw/r16/Huu+8Wo+W28+V/R08/ttOnT4vLsbGxsn9/W5k7xvDwcHE5JCTErn0r/fzzz+jRo4fstujoaNl6vXr1sHfvXgBFF0x0xvN6+r+jM/jDMaqxOXxERETILqmcl5cHnU5nsp3BYMCsWbOwcuVKhIeH47vvvsPcuXPx6quvqu43ODjYa4OGJQEBAT7/QnL1Md69exdBQUEu278tinOMtgyyEwQBJUqUkN12584d2XNIuyHPnDnj8teRL79WPfXYpK+VkJAQh9qoPEbp57TxfkdFR0eb7Ef5Oi5btqy4XFhY6NS/u6f+OzqTPxyjlM1HGh8fj6NHjwIoCh7JyckmyRcAbt26hbt374rpu06dOjhx4oRzWkt+Y/bs2YiMjMQ777yjdVNsZsv1OgoKCqDT6bBy5Urxtps3b8q2kfaVS7ty7t69i//85z8YOHAgzyDzcq4ccPrPP/+Iy8oqm73UxncEBwcjMjJSXH/ggQfEZZ7tQtbYHD6aN2+ODRs2YOfOnZg1axYaNWqkei54VFQUrl27hp07d+Ls2bP48ccfbe4DIv909uxZjBw5UnY5+tdffx25ubn45JNPNGxZ8aid7aJkDCjdunUTb7MUPi5cuCAuL126FN988w0WLlyIjz/+2MHWkpakQdXZ4WPYsGHisrELz1FqbdTpdPjuu+/wzDPP4IsvvpC9phk+yBqbw0dkZCQmTpyI+fPnIykpCaNHj8bmzZsxbdo02XZBQUF455138Mknn+DFF19EQUEBBg0a5PSGk+/o3LkzZs6ciZYtW6re7y2jwG0JH8YP5eDgYJQsWRKAafiQ/sqUDk6VnrI+ffp0R5pKGnNl5WPs2LEYMWIEfvnlF9StW9fu/QwcOFBcrlOnjuo2PXr0wLJly/Daa6/JXreuumov+Y5iXXGoUaNGWLRokbjeoUMHdOjQwWS79u3bo3379g43jvyDdPBdfn6+yYdxdna2U6994SrFqXwAQOnSpZGRkYFTp05hw4YN6NSpEwD5xeikM6CWKlVKXM7KysLEiRPx3nvvqY69Is8mfa04e1zTfffdZ3FKf1tNmzYNDz74IJo3b27T+09aCWflg6zxn9Et5BXUzhhRDqDzVNJgMXbsWFnfu5H0Q7l06dLicufOncUuFuWVcI37vXHjhuz2999/H/v27XO84eR2rqx8OEtMTAxGjhyJpk2b2rQ9wwcVB8MHeRS1oOEt4UP6hRIVFYWGDRuabCMNKNK5PQRBECtAyvBx69YtAPK5IYzOnz/vWKNJE64c86EVaQWH3S5kDcMHeRRvrnzY8mtW+qH87rvv4qWXXhLXjWewKMPHzZs3UVBQgDNnzpjsTzlhGXkHb6h8FBcrH1QcDB/kUbKysiAIgslt3sCWX7PKX4T169cXl82Fj5SUFPTr1081mCkHq5J3cOWYD60wfGhv9uzZ6Nu3r1dcW4fhgzzK6tWrZaeXAt4TPmz5QlF+KEtnCDZOTa0MH1u3bpXNCzJjxgxxmeHDO/l65YPdLu537do1vP7661i+fDk6d+6sdXOsYvggjzJp0iTUqFFDdps3hg9bKx/Si8yZq3ycPHlSXH788cfRtWtXcZ3hwzv5+pgPVj7c7/r16+KycUJQT8bwQR7PW8KHLV8o0hkhAdvCh3RQ6ZNPPik7S4bhwzv5euWD4UN7lq4m7wkYPsjjeUv4sKXbZe7cubJ1W7pdpN1QUVFRiIqKEq8BwQGn3snXx3yw28X9lH/z48ePa9QS2zB8kMez5WqxnkDt1+xDDz0k3rZixQrZAFPAtsqH8VRbAGLwMFY/zp49i0cffRQlSpRA7dq1VecWIc9y8OBBLF++XFz3lcoHu120pZzk8M6dOxq1xDYMH+TxvKXyodbtsnLlSrRu3RojRoxA7969TR4jrXyYCx9Sxm6bmJgYAEB6ejp2796NnJwcnDlzBrNmzXL8QMhl1q1bh4YNG+LatWvibb4SPtjtoi1l5SMjI0OjltimWNOrE2nhvffeQ5cuXWRVBE9z8uRJTJgwQVw3/gqsVasWtm/fbvZx0spHTk4OCgoKLF7LJioqCoDp2BGjs2fPFqfZ5GafffaZbD0qKkp2IUFvxm4XbXlb+GDlg7zCqFGjtG6CRaNHj5atSysalii7XSxVPYB7ocNc+FCepkyeIy0tDb///jsAoHLlypg6dSp27drlFdctsoVOp0NgYCAAVj60oOx28fTwwcoHeQW1qcU9yaVLl8TlJk2a4OGHH7bpccpuF2vhw1rlIzk5Gbm5ubJQQ54hMTFRnECvXbt2eOuttzRukfPp9XoUFhYyfGiAlQ8iF5Cm+qysLPTs2RM9e/aUXfVVS8bxGgCwd+9eWQnaEmW3i73ho0yZMuKyNAiRZxAEQRY2KlSooGFrXMf4ume3i/sxfBAVg3R8Q0JCgtkvbemX8oIFC7Bq1SqsWrUKY8aMcXkbbWFsX7ly5Yp1ifvidLsEBAQgPDwcwL0QYjRw4EBxOTEx0ebnJ/f4/fffsXnzZnG9fPnyGrbGdYxjnVj5cD9v63Zh+CBNST+kAgMDUaJECdXtpF/Ku3btEpfnzZvnusYVg7HyUdzuDmm3y7p169C+fXuz25YvX14MNpYqH5x4zPOsWLFCtu6r4cP444Hhw/28rfLBMR+kqcLCQnFZr9ejRIkSquenS8NH9erVxWVP63YpbvhQbi89W2XgwIGoWLEifvrpJwQHB+Odd94R71NOTBUbGysuM3x4HuUZLb4ePtjt4n4MH0TFYGvlQ1lSlDIYDOKMn1oxhqOQkJBiPU6v10Ov16v+UuzVqxeefPJJ2Sm8RsrTcaVTrnPWU8+j7E701fDBbhftsNuFqBjUKh9q8vLyxDMFlDOeWhuk6WqCINhd+TD3mKtXr+LJJ580+xhl+JBWPhg+tPfHH3+gevXqeP311wGYTpQXFxenRbNcjt0u2lFWPv7++2988cUXGrXGOoYP0pStlQ9BEMRtPS18SH9x2BM+lDNcDhw4EPfdd5/FxygHtTJ8eJY2bdrgwoULmD17Ni5evCgLH+PGjbN5Hhhvw/ChHbWurhEjRuDGjRsatMY6hg/SlLLyofxQlparP/roI/z4448mvyKlp7lqQRp+itvtAsBkkqmZM2dafczQoUPFv82yZctk4SMlJaXYbSDXyczMlL1me/TooV1jXMzY7cIxH+6n1jVtMBhw9epVDVpjHcd8kKasVT7i4+Nx9OhRAMD48eMBmJ5mqnXlQxp+7Kl8PPjgg7h8+TKAouM1N4GYVFxcHPbv34/k5GR06NBBnF2ysLAQW7Zswblz51CjRo1it4WcLzAwUDYw2lx1zxew8qEdaeBr2LAh/v33XwCeWwll5YM0pax8KLsbpGe2GKWnp8vWtQ4fjlY+Pv74Y3HA7NixY21+3EMPPYQnnngCAQEB0Ol0sqqR9KqppK38/HxZ5cM4V4svYvjQjjR8SCex89Sz3xg+SFPKykfLli1l99vSN651+HC08vHQQw9h8+bNWLx4MZ599lm72/H++++Ly7dv37Z7P+RceXl5fhM+pN0uxgHi5B7SbhfpjzhWPohUHD58WFzW6/Vo1aqVuF6rVi2bKgneHj4AoG3btujXr594YS57dOjQQVxWmyuFtJGXl+d33S6A6RlZ5FrmKh8MH0QKhYWF6Nmzp7geGBiIatWqYdy4cahbty7mz59vU/jQesDptm3bxGV7ul2cpWTJkuIyw4d2lF+60spHQECApq8RV5OGD3a9uBfDB5GNlLOTGj+4PvzwQxw5cgStWrUyOQ1VjZaVj4KCArzxxhviupZXk5UOVPX0CYZ8mfJsLGn4CA8PL9a1f7yNNHzwjBf3kna7cMwHkQXKPmG1LgdP73a5deuWbF3L8MHKh2dQBj9l+PBl0mn/WflwL2nYk475OHXqlBbNsYrhgzSj/HBSu6Ktp4cP5cBOLUvqISEh4vMzfGhHGT6GDx8unkrty+M9AHa7aEkaPkqXLo1GjRoBAP7991/s27dPq2aZxfBBmpGeZgvYX/l46qmn8O6775qUu91BGT60LjUbqx8MH9pR/u2lkzxJr8Hji9jtoh1pt0tQUBCee+45cf2RRx6RjU3zBAwfpBlbKh+2jPkAgClTpuCHH35wSruKQxk+tO5fNY77YPjQxunTp/HII4+Yvb8487h4I2m3i6dccdpfSMNeUFAQ6tSpI7u/X79+7m6SRQwfpBll+LC38mEkvRy9uyjDh9Yjy43hgwNOtfHNN9+YvW/r1q3o3r27G1vjfrVq1RKX//jjDw1b4n+k4SM4OBiVKlWS3X/t2jV3N8kihg/SjLPGfBilpaU52qRiU4aNhg0bur0NUsbwkZ+fr/n8J/7o3LlzZu+rW7euG1uijS5duojLGzZs0LAl/kdZ+VCGD0/D8EGaUY75UOPJ4SMzM1N2mi0A8RLqWuEZL9q6dOmS2fvKli3rxpZo45FHHhEvFXDhwgWNW+NflGM+lNeIUl4TS2sMH6QZZeVDbYCarWM+APeHj19//VW2vmPHDs1PpZR+4DB8uN/FixdVb/eXa+0EBgaKg2rVrq589+5d/Prrrzh+/Li7m+bzjAPudTqd6udmTEyMu5tkEcMHaUYZPtQuCV2cL3N3hw/lF010dLRbn18NJxrTTnp6uvgaNP76N2rcuLEGLdKGscKjFj6++eYbPPXUU2jatKkm3aS+LDk5GUDR3984fu6XX34R79fibEBLGD5IM7ZUPmJjY01u0+l0qv2Z7v4wU5aV1a7A626sfGhH2uVSu3Zt2X2eEEzdpUyZMgCAnJwcky88Y7dkZmYm1q1b5/a2+SqDwSCGD+kEYz179sRDDz0EwPRq4Fpj+CDNKMd8qFU+lPMidOvWDYWFhVi5cqXJtu4MH6+//joWLlworu/atUvzLheA4UNL0vBx//33y+7ztP52VzKGD6Co+mEwGFTHdzlyEUWSS0lJEf/G0vAB3Hvt5efna34dLCmGD9KMPZWP0qVLQ6fTqZ7JkZaW5pbLeF+5cgWzZ88W16tVq4ZHH33U5c9rCw441UZBQQFGjBghrisrH2pncvkqafi4ePEi6tati0qVKuH8+fMatsq3JSUlicvK8CGtun399dc4c+aMu5plEcMHacaWMR+lSpWSrVeuXBmAfDIjo8LCQrf0ayorLJ9//rnLn9NWHPOhjQ0bNsi+XJWVD38iDR+PPfYYTpw4geTkZLz00kuy7RiOncdS+JBW3f773/+ibt26+PPPP93WNnMYPkgz9pztYgwfzZo1Q9OmTREUFCTbRjnplytIZ258/fXXZXMbaI3dLtrYvHmzbF1Z+fAnVatWVb19165dsnVPG4Pgza5fvy4uly9fXnafsus6Pz8fU6dOdUu7LGH4IM0o+4FtuRaEMXzodDrs2rULKSkpsl9U7pjeXBo+PO1CYQwf2qhSpYps3dMneHKlPn364OGHHza5Xfl+1yp8CIKA27dv+9QkfDk5OeKycuzZCy+8YBJITp8+7ZZ2WcLwQZqxpfKhFBcXJy4HBAQgKipKNi7EHdObS9/oYWFhLn++4lCO+RAEAd9++y1mzZrFC325kPRv265dO5MzDvxJiRIlVAeEK2kRPu7cuYMHHngApUqVQqlSpUzm6vFW0oGkys+khg0b4sqVK8jIyEB8fDyAorE4BoPBrW1UYvggzSjDh/S6EFIdOnQQl5W/MAG4PXx4S+UjIyMDCxYswKBBgzBixAjZOf/kXNJf0W+++SaCg4Oxf/9+TJs2DXPnztWwZdoIDQ21uo0W83xs2rQJJ0+eBFD0Pv7444/d3gZXkP4gUvvbBwYGIiIiAjVr1gRQ9Ho1npqrFf8Zgk0eRxk+JkyYoLrd3LlzMXPmTHTq1En1y56Vj3uk4WPhwoUmpwM/88wzWjTL50kHSxvHIDVu3NivJheTsuWyCFpUPjIzM2Xr+/btw/Xr11GuXDm3t8UWV65cwc8//4y7d++ia9euZgcySysfloJftWrVxOULFy7IKsnuxsoHaUbaBzxlyhSzEzFVqVIFn332GTp27Kh6Pysf95QqVcrsh48/zTXhbtLKR3GuR+SrzL0GO3XqJC5rET6kPxyMdu7c6fZ22EIQBHTt2hUjRozAqFGj0Lp1a7PjVGwNH8bKBwDNp7hn+CDNSCsfaqfO2ko6mjs1NRWFhYUYNWoUXn75ZdUPG0d5cuWjRIkSmDNnjup90tBEzqVW+fBn5v4Gs2fPFu/TInyoTbJl7IbxNMePH8fBgwfF9evXr+Py5cuq29r6mdSgQQNx+d9//3W4jY5g+CDNSMOHI7MdSisfN2/exNatWzFt2jTMmzdPNvGTs3hy5QMABgwYIBsnY8Tw4TrS8MHKR9FgcGUAeeONN1C9enXxbAwtrjXiTeFjw4YNJrepXS8HsL3yIQ0f//zzj/2NcwKGD9KMNHw4MgOksvKxe/ducd0Vg/08ufJhpDbVO8OH60jL4ax8FFGGsLfffhsAEBERAYDhwxrpdP1G5rqVbQ0fkZGR4sD+Q4cOaXoGHAeckmakYz4cCR/GDzOg6AtWeYE3g8FgcpVRR3h65QOQ/02MGD5ch90upkJDQ2Wz7BrfK55W+VBeINJTqP19zFU+ivODqEmTJggICECjRo2QkZFhMou0uzB8kGacVfkIDAxEUFAQ7t69i5ycHJPJjG7cuGEyyY4jpF/inlr5YPhwLw44NaX8O6iFD0EQoNPp3NYmtfCRnp7ulHacP38eiYmJePDBB1Wvxl1cyjNzAMe7XQDgxx9/dOqPMXtp3wLyW84a8wHcCwHZ2dkmp/A6e2Cb9FeGp1Y+2O3iXqx8mJJ+Cer1enFQufG1aTAYkJubi3379uHXX3+V/Whw1QRY0i9p4y/+goIChwemv/POO6hRowbatGmDuLg4nDt3zqH9Aerhw9FuFwAeETwAhg/SkLMqH8C98JGTk2MSPpw9mRErH6TEyocp6d9BGoalyydPnkRCQgKeeuopLFmyBAAwbtw4lChRAtOmTbP5uU6fPo0JEybg1KlTFreTfklL5/Zw5FIES5YswSeffCKu5+fnY+PGjXbvz8hVlQ9PwfBBmnHWmA/gXgUiJyfHZBCVP1Y+1MKHK047piKsfJiSfglK3yfS1+asWbPEHwsvvPACrl27hkmTJiEvLw+jRo2y+bk6dOiA8ePHo2XLlha3Mxc+HPmMkAYPI2fMN6QWPm7cuKG6rfG9HRwc7DGVDWu8o5Xkk1j5cB12u7gXw4cpaeVD+jeRvjaVX/rLly+367mMZ4aYqwwYSQO4syofiYmJJrdZa4ctjOEjOjpa7LIyNyW6MVR5S9UDYPggDblqzIey8nH48GGH9q105swZAEW/5tS+5D0Bu13cy9jtotfrveaXp6tJJw6UhnTpe0Z6NgwAp4yVsDReRFr5KFu2rLhsb+XDYDCIj1We8i8Igl37NDKGj5IlS6JChQoAgKSkJNVtGT6IisEVlQ+DwWDSvTB58mTVc+btkZSUJM4y+Mgjj3jsF41amDMXPsyVcsl2xsoHqx73SLsNYmJixGVp+FBWDZQhwJ55KCxVMZzd7ZKZmSmGHemFMZcvX47w8HDVLpni7Bso+iFhvEpySkqKrMpmZPzM89RKrJpifXIuW7YMHTt2xODBg3H79m2r23/yySdYunSp3Y0j3+aKMR+A6a8pAJg/f75D+zfau3evuPzoo486ZZ+uoPahnZmZiWeeeQYNGjQQf2FOmDABFSpUwMiRI93dRJ9irHxwsOk90u5O6XWbpOFDWelQhgBb5gJRVhgsdbMaw0dAQICsUmFvt4v0uSpWrCj798/JycE777yDcePG2fR9KSUIgmr4AICPP/7Y5BovPl35OHnyJJYsWYLly5ejb9++Zq8fYXT27Fns3r0bTz/9tMONJN/kisoHoP5B4si1Y6SkfbnKycw8iVrJt6CgACtWrMChQ4fQr18/CIKA7777DgAwc+ZMdzfRJ+zZswd9+/YVu+JY+bjHXPiQdgkq5+RRdiuoDbpUUlYCbAkfoaGhsgst2lv5kD5XTEyM6vwekyZNwpgxY4q135ycHPE9rAwf48ePR2hoKOrXry/+Z/zM86bwYfMn/o4dO9C1a1dER0ejbdu2mDdvnsXtZ8yYgSFDhlj90M/Pzzd58ej1eq99ExtLcK46T90TOOsYpb/OdTqdQ/uTvunUPkgCAwNx+vRp3L17F3Xq1LG6P3PHKP3FERQU5LH/zt26dUPJkiVVq0BAUQVH2d3iqcdiD3e9D1999VUcOHBAXL99+7bb/o6e/lkj/WKOiooS22mpa+DIkSOy9YyMDJQoUcLiMSq7WW/dumV2e2n4KFmypHh7enq6XX/HW7duictRUVGIjY3F1atXTbbbv3+/2f2r/TtKf0CFh4eLYz6klH8rYxu0fj3Y2hVtc/hISUlBQkICgKIvCr1ej5ycHNUX0s6dO3HgwAGEhYXhxIkTGDp0qOoAOABYuHChSZDp3bs3+vTpY2vTPJLaCGhf4+gxSt+4N2/edGhchvQXlNoYhj/++APjxo2DIAhYtWoV6tevb9N+lccoHW2ekZHhtLEkrrBu3TpcvnwZFy9exLhx40zu37Fjh2zdk4/FXq5+Hyr/Zvn5+W7/O3rqZ430PRkQECD+XcxdFh4wnYH03LlzqFevnsVjVJ7WeubMGVSrVk11W2M3TlBQkKxLZ/z48Vi/fj369++Pbt26mX0updOnT4vLgiDggQcewKFDh0y2u3r1qtXXhfQYpVev1el0svEkRsrv3ujoaDz//POav4/N/e2VbA4fBoNBFiBCQ0ORmZmpGj6+++47NGnSBD179sSqVaswYcIETJ06VXW/AwYMQP/+/eWN8vLKR2JiIipVquSxgxEd5axjlPb9xsXFoUqVKnbvSzpyXVnKBYD//e9/4vKkSZOwZ88ei/szd4zObLOrSdtWvnx5DBkyRHb/8OHDzW7v7dz1PlR7rbnr7+jpnzXx8fHiRdsefvhh8e9Sr149m/dh/M6xdIzKadGDgoLM/hsYq+wRERGoUaOG7L59+/bhxIkT+M9//mNzN610u2rVquGjjz5SHeeYkpJi9hjU/h2lP3Li4uLw1FNPoU6dOjhx4gTKli2LK1euOHyGoNZsDh8RERGypJiXl2d2LvyjR49i+fLlqFy5Mh544AGLSTI4ONhrg4YlAQEBHvmB4EyOHqP0g9vRyXGkA06tDR7Lysqy+bmUxyjtIgwLC/Oaf+M2bdqY3KasEHnLsRSHq9+HamceuPvv6KmfNYsXL0anTp0QHx+P5557Tmxj5cqVbd6H8TvH0jEqB1ffuXNHdduLFy/i5s2bAIoGBku7XYwyMzORlpYmOxPGEulnTUxMjNnvsoKCAty+fRtlypQxuy/pMUpnar3//vsRGBiI5cuX48svv0S/fv2cNoZNSza/YuPj43H06FEARcEjOTlZNohIKjo6WvzHCw4O9ti5EEhbrpjnAwAOHjzo0L4s8dZptG35wHd0XgJ/pBY+qEijRo2QlJSEP/74QzagvGLFijbvw5YBp8quGml3rtRXX30lLjdr1szs91KXLl0sjpsQBAG7d+9GcnKy7CwWc9+HRteuXbN4v9Tx48fFZeMYtXr16uHrr79Gq1atbN6PJ7M5fDRv3hwbNmzAzp07MWvWLDRq1MjsGQoPPfQQNm3aBAD45Zdf0KBBA6c0ljzb+++/jzp16uD333+3aXtnnu3iri9Obw0far/ISpcuLTsGtdNzV65cifvvvx8ffvghw4mCIAgmf7O4uDiNWuOZ1H5UhIWFyU5ztcSe8DFx4kQ89thj+OWXX2S3S8dUvP7662YvjbB//36sXbvW7PMtWrQIjz76KOrWrSs7VVja9WskPX5zs5NKff/99xg0aJDsuja2DJD3RjaHj8jISEycOBHz589HUlISRo8ejc2bN6te/OfNN9/Epk2b0L59e2zZsgX//e9/ndpo8jzZ2dmYOHEiTp48ibZt29r0GGfO8yE9bc6VvDV8AEUfbNWqVUNCQgI6duyI1atXo3HjxuL9auFjypQpOH36ND744AOsXLnSnc31eMqqR6dOnfDrr79q1Brvoqx+qHULArbN86E2gHX79u0YMmSILDBLqxSVK1e2WJGXVh6UBg4cCKCowvLjjz+Kt5cvXx4A0L17d/G2Tp06icvWKh87d+7Eiy++iG+//Va8LSwsDJUqVbL4OG9VrE/8Ro0aYdGiReJ6hw4d0KFDB5PtypQpgy+//NLhxpH3UM6emZqaqnrOu3IbI0fDR/fu3W2+EJW5sUq28Obw8fzzz+P5558X1w0Gg6zvOD8/3+QD+Z9//hGXt2/f7vVnoTmTNHy0a9cOv/32m4at8S5NmzYVzwrR6XSYMWMGPvnkExw8eFA23sGWaoGy8mF069Yt5Ofni+9TY3eMTqdDVFSUxXEy5s7OtMRY+fjqq69QWFiIGjVqoFmzZli3bh0AiONNzPnhhx9MbqtSpYpDn1eezPNGKZFXUv5q/uuvvyxuP3HiRKxevVpcd3TMR61atVT7Qnv06OHQfpW8OXyoUYYPSyydIumPpH8vX3gtuNOUKVMwc+ZMjBkzBps2bULDhg2xbNkynDx5ElevXhWDwcqVK81292VlZeHxxx9H+/btzT6PdA4QY+UjKioKgYGBFr/UzQUac0qVKiV2bVaoUAFr167FZ599Jhtgau1ic1u2bDG5TTq5mK9x7Ocm0f9TfnGZm9zK6OuvvxaXQ0JCrFZJbCG9foTR559/joiICFl51BG+HD6sXUeD4UOOV7K1X0xMDEaMGKF633333YfWrVtj27ZtuHDhAq5fv46qVauabLd69Wps27bN4vPk5OSIA0GN4UPtc0KpuNOhmzs7Rvq5ppyPRMkZV8L1Jqx8kFMow4e1LzLp7IeLFy+2OlLcFmpTCwcFBZn8MnJk4KSvhQ9pd5e1ykdxfw36OoYP15EO3FXOYGpkywURjY8VBMGl4cM43kPJ1vBx9+5d1fEt0kH5vobhg5xCGTYshY/CwkJxjEizZs3Qq1cvp7RBLQzo9XqTXyXmPsxs4WvhQ/qlycpH8TB8uI70h4Ta666goACLFy+2uh/jez0zM1Mc4O6K8GHuLCe18LFv3z7MnDlTFp7MzU00bNiwYrXDm7DbhZyiOJUP6elzahP92Eut8qHX601+lVjrErLE18KHpcqHcvZOVj7kpK8Fhg/nkr6X1SpyX331Ffbv329ye7t27XD37l388ccfAO4NhJfO/VGqVCnV5/z666/xn//8B4Dli9OpadeunertxsnMMjIykJKSgtzcXHTs2BG3b9/G1KlTcfjwYZQqVUoWPvr27YvatWtDr9ejd+/exWqHN2Hlg5yiOJUP6Ze/O8KHsvJhy9wB5vha+LA05kP5i5OVDzkOOHUda5UP5aUBjHr37o1HHnlEXDdWPsxdYVdKWhExV/lQm05fr9fjySefVN0euFf9uH79Oq5duybuOzk5GX/++ScAeeUjNjYWEyZMwLhx4zxy5lpn8d0jI7cqTuVD+kaLjIx0WhvUvgCCgoJMpjTOy8uz2sVgjvGDUK/X+8QHg6WzXZQf+qx8yLHbxXWshQ9zbt26JZvt2Bg+pFMBmJvfQ6/Xi/MFmQsfyh8urVq1woIFCyxOm268hszt27dN5oExfhZKL0bnjPFv3sD7Pz3JIxQnfLi78hEYGIjRo0fLblfOS2Ir4wehr/zSLU74YOVDjuHDdaTvr+K87mJjY1XDhy1VKp1OJ1YpzJ15Iv3h1KtXL/zxxx944YUXLLZJOm5DeQX3jIwMZGVlYfz48eJttoxJ8QUMH+QUntrtYqxOfPLJJ+jatat4O8NHEUvdLspKBysfcgwfrlPcykdcXBweeeQRPP/887LwYXyfmxuf07NnT3G5YcOG4viwtLQ01de7PVXbzp07i1O5nzhxwmR/ytlU/aXywQGn5BTWKh/Hjh3D77//bpLqnRk+lIFAr9fLJhKSzlrI8FHE0oBTVj4s45gP17E24FTp8uXL0Ol00Ol0smu2WKt8fPXVV6hcuTIeeeQRVK1aFRUqVBDvu379OqpUqSJ7HukPJ1tnQQ0ODkazZs1Ur3mVkZGBpKQk2W3+crFChg9yCkvhIyUlBY0bN1b94nZl5UM5Zbvah1Jx+Vr4YOXDfjzbxXWKW/mQjr+SVj62bNmCAQMGmB0oXq5cOXz22WfiuvTMuGvXrpmED+nnhrkL06l56KGHzIaPq1evym577LHHbN6vN/Ob8PH333+Lc+s3a9bMKTNq0j2Wul2OHDkie/NLl10ZPqRfrID8w4KVjyLSL01WPoqH3S6uYy18BAcHm60QSMPHsmXLULJkSdkXuqV/K2nlQ+26MtLwIX0ea8xd+DIjIwNXrlwR11977TXcf//9Nu/Xm/lN+BgzZgy2b98OoKhcdunSJbPne1PxWap8WPqi16rywfBRRPo3YuWjeBg+XMdSt0thYeG924LK4Ydv5VdWV4aCefPmISEhQVy39N5VVj6UnB0+vv/+e9n6q6++avM+vZ1fDjjNzMzEnj17tG6GT7FU+bD0RW/pstbFpTbmQ0ptIFpxZGZmiuFDbXCrN1I720UQBKSnp6tWPhyZmt7XMHy4jqXKhzjuos5KoFkSLgv9ZferhQLp1Oa2Vj4SExNN7rc3fNgyODUgIAAVK1a0eZ/ezm/Cx6BBg2S/fO2d54HU2Vv5cOaHtqvHfGzatEn88m3cuLEdLfQ8agNOhw8fjujoaJMLfwmCwPeNBAecuo7V8BEYAcQ+BQAYO08eiNX+LU6ePGnxfqPatWuLy8ozUwDXhY+IiAiMGTPG5kGsvsBvul2ee+45JCcni/M98EPUOZYvX469e/eaDL6yNXwox2U4ojhjPp5++ml07NgRsbGxGDt2LOrUqWN1///73//E5e7duzvYWs+gdm2X2bNnA4DJKYBA0RcBf+UXYeXDdSyFjzt37gChNcw+Vm0WUmmQsPRvVbVqVYSGhiI3Nxdr1qxBdna27HND2vXorPBRs2ZNbN682WRwq6/zm/ABWB5cR8V39epV9O3bV/U+LcKHtW4XZUDatGkTgKL2/fLLL1b3f+rUKXG5adOm9jbTo1iaZExNbm6uU8fpeDOe7eI6liYZu3PnDhBWS3ZbVo6A8LCi0+offfRR1K5dG6dPnxbvl753LVU+AgMDUadOHfz7778oLCxE2bJlsXPnTjRo0ACAayofdevWtXk/vsRvul0Ay6cVkmUGgwF//fWXbJKdf//91+z2nlD5sDTmQ+rSpUs27f/s2bMAimZR9JWJgCwNOFXDM17uYeXDdSxVPq5fv25S+bgquVq9Xq/HkSNHsGDBAvE26YXlrP1bNWvWTFzOysrCSy+9JK67Iny0aNHC5v34Er8KH6x82O+DDz5AixYtUKNGDbGEWVBQYHZ76RdZVlaW2e2cGT7i4uJk5/srB2+ZOy/flqvcHjhwQDwlrmbNmg600rMoKx9qJWspnvFyz8WLF8VlVoOcy1L4SEpKAsLk78GritnQg4ODZd0Y0oHS1sbnjB8/Hm+++aa4fujQIfEHlDR8FGfQuVr4iI+Px6effupXZ7hI+W34YOWjeIwT5KSmpuLDDz8EYP76B4DtlQ9ldcIR9913H3744Qc8/fTTGDBgAGbNmiW7Xxk+jFe7NV4s6rfffsN3331nEqq2bduGJk2aiOu+FD6k74nc3Fyr7wuGjyKCIIjddqGhoXj44Yc1bpFvsXSqbVJSEiDIb1v8PwF9PjBg+7/WQ4a1ykfZsmUxbdo0WZeycRZSZ1Y+1q9fj1GjRvlt1cyvxnwUt3+b7pGe83706FEAzgkfzqx8AEC/fv3Qr18/1fuU4aN06dK4fv06kpOTMWjQIHz77bcAivp9pfswfskYtW7d2qlt1lLp0qXF5aSkJKvh49KlS07ro969eze++eYbDBkyBAkJCbhy5QrOnTuHli1bevwVg5OSksRKWIsWLYr1RUTWScPH9u3bER8fL66fOXOmaOHmeqDuWgDAgvVFN63cJkDYUTT2w9yXuq1nJt13333i8tWrV1GzZk27B5xGRERAp9PJKjD+/prx7He4k7HyYb/AwEBx+fTp08jPz/fI8GGJ8s0uPa3NGDwAYPPmzbLtpOf7T548WdYH7O2kH7CJiYmyUF67dm3s3LkTc+fOFW/bvn07hgwZgjFjxjg858ejjz6KRYsWoXnz5sjIyEDDhg3Rpk0bzJkzx6H9uoP0NS2dmIqcIzw8XKyKZmdn48yZM+J/ovTfER5q+ho0vi7NhQxbw0dcXJy43KZNG9y9e9fuykdAQABq1Lg3TiUqKspvrl5rDisfZBPpuI2CggJcuHABN27cMLu9J4YPZXeKuX56ZV+udPrjN954w6ldRVqLiopCiRIlkJ2dbRI+HnzwQTRv3lz25Tpt2r3ZJLt06SKbOdIRa9euFSeCev311/Haa685Zb+uIn19u/M17C9KlCiBCRMm4IsvvkBubq5YCZMOHIUhF4830mHtLvljJ38PxEYLaFVLvfJhazeHNHwARafa2xs+AODHH3/EN998g4KCAjz33HM+M1GhvVj5IJsoB40mJSUVjTo3wxPDR/Xq1cXlTp06mZ3Q5/bt27J1Y+UjJibGqTOyegKdTodKlSoBKLoyqNrpo9WrV5fN/Ggk+xXqILXZJD0Zw4frjRkzBlevXsU///yDlJQU3Lx5E4IgYMiQIQCAvn37oo7K1BjjFgh4ZbqAPaejVfdra+VDWdE6cuSIQ+GjadOm+Pbbb/H999+jQ4cOxXqsL/Kr8MHKh30EQRAHZRolJydj586dZh+jxYBTa0qXLo1Vq1bhzTffxLfffmu28vHTTz+hY8eOeOGFF9CxY0dcvnwZgOnZM77CeFzZ2dmyQGl8v+h0OowbN87kcWPGjJGdeu2IvXv3OmU/7sLwoZ2vvvoKp0+fxuLFi3F/ZZ3Z7Q6cVT+7zdbKR6NGjWTrjoYPkvOr8MHKh33UTsH83//+Z/FvKA137jrV1hbdu3fHtGnTUL58eZPKh3Rcy5YtW7Bz505s2bJFPHZjhcDXVK5cWVw+d+6cuCx9vwwdOhQzZ86UPS4pKQljx451Sht27NghW7f3wn+udP78eXz44Yc4fvw4w4eGAgMDUatWLQQEBCC+svntvlxTEojtZXK7LZWP5FQBYWERsure0aNHZQNO/b3bxFF+FT5Y+bCPsuoBADdv3rT4GE/sdlFSfghZuspxZGQkhg0b5uomaUIaqsyFj4CAAIwYMQI//PCD7LHGqdiLSxlmpRf+AjyzG6Z79+744IMP0KZNG9nnB8OHdupWt7JBnRVAmPwS9cHBwRj/rQFNhxqw/6TpgNUfNwuI6yXgkaECqlevIYbzpKQksfIRFBQk+7FCxedX4YOTjNlHrXIhLberdUdIw4elSby0/OCWBqiIiAiT8DF79mykpaXhzp07SE1NRefOnd3dRLeQ/vuZCx9Gzio1W5sp1djV5Umkp5hLX9/+Ok+DJ4gM1+EJa1c6KN1NtnotLQQTFgF7TwDdx5iGj+cnCRAE4N8zwIFT9+YDSk1NRVpaGgDnXo3bX/lV+OD06vZRq3xIw8f8+fNx8eJFnD59WhyYaEv4CAwMhE5nvs/W1aRzl5QvX97k1LeoqCiULFkSJUuW9Olft7ZUPozcFT5snfL+5MmTuP/++1GrVi2sWbPGGU2zifQ94cuvDW+weJwOvR8rWm72IFBfec05QX6WW/LNexWLJEnBLSVNwPOTDLJts/PuhQ9BEHDhwgUApmfCUPH5Vfhg5cM+apWP9PR0cTksLAxVqlRBrVq1xL+xMXwYDAazYz60PmW1d+/e4vIrr7xiUvnwl1+00jEf0kHE7g4f0omkbK18LFiwAKdPn8bZs2fxyiuvOKVtapQzu0q7iRg+tFUqUocVEwIg7AjA318F4LGGig30pYDqnwFVJiI4JBRXUuQ/eO4WCDh6XsDcNcCP8il+cDO9aMZTJX+7Aq0r+M6EBTZg5cM+apUP6QRT0plDjX9j499XGjxCQkJkXzpaf2i/9NJLOHbsGAIDAzF8+HCTMy78JXxUqlQJQUFBJu8JV4SPO3fuICIiQjX8r1y5EvXq1QNge/g4cOCAuGycAtsVlKdfM3x4rirldQAk3SmVx4iLd+OGod+H8q6W9iMF/HFQfV830u5VPmTPwfDhMFY+SObKlSuYNm0aPvroIxw7dgyXL1/GlClTLD5G+oWkDB/SLhflm1jrD+3g4GDMmjULM2bMgF6vN/litXU+AG8XHh6OqVOnmgygU/v3sTV8JCcno3///vj444/F2zZu3IgyZcqgUaNGqoFWWoGxJXzMmzcP27ZtE9fNzdtijSAIOHr0qMXPBIYP71HKwjX+hMBok9vMBQ8AuHEb0JW4HwiMkt3O8OE4Vj5I5umnn8aePXsAAGPHjlX9RawkrXwYA57xg1wZPqRfKp72oa38YvWXygdQNHNrv379ZCVmeysf169fl03b3rp1ayQkJKBfv37Iz8/HoUOHsGLFCpPHRUZGIjIyEnfu3MHVq1etPs+XX34pW7f3onfvv/8+Jk2ahFatWmH79u2q45CU4UM6WNnTXsf+rvp91rex1fx1AhJvPA883AnYWx0wFFVyq1Wr5rwn8VOsfJDM4cOHZeu2hDTpF5JxFHh+fj4KCgo8uvKh5K+VDyPlpGv2ho8XXnhBtv7XX38BkH+BHz9+XLbNN998I2uDpblhjA4dOiRbLygoMJlC3+j8+fNo27YtatasiV69eslel5MmTQJQNNeIMmQYKW+XXtfI017H/q5FfaBvW+fsK9F4BYmgWKDscwCABxJeRzK6IzfP9EyZ9EwB328UcOma+nWPBEFAYaFj10TyFX4VPlj5sEwQBLNnIYwcORI///yz6n3Syof0FLSsrCzZh7xy4JbWA06V/LnyAZiGLXvDh/LCfGoViV9++UVcjo2NxcCBA2X7l84kaY50gKql5wKAzz//HL///jvOnTuHX375BT/99JPqdsqzbE6dOoUNGzaYTILGbhfPpdPpsPSDADR70Ln7nTxlBi4k3cXxwM8wYnYQvvjFdJv/zhbw4kcCOr4lFH2e5t8LGneyBDz4goCqfcyHE3/iV+GDlQ/LCgoKYDAYTG7X6/WYNGkSateurfo4tcoHUBQ+pH37rHx4NmV3g63hw9rVbY2BVvrvLZ1kbNCgQWIQNe7fli4UtYBi7nHGUySNzF2R+eLFi+LyqlWrEB8fjyeffBJTp06VbScNH/4WUr1Fq/rm77NUGenzGNCwluntYWFhWL3z3rio0V8JeOdrAxoNujdZ2cLfiu47dRlYtAEo1UVAt3cMEAQBn60ETlwCrqQA/5kuYM6vAkZ8bsDt//99VlAA7Dsh4G6B+vvp5KV7oUUQBNn7zmAQcPm6dwUavwofrHxYZu6D+7777kNYWJjql3FgYKDs71qcyoenhw9//1KxNXxYq1IYX1fm/r2lryvjlNU5OTlWQ43a86rddu3aNZM5QIzbKWdalYaP//3vf2afWzofiqe9jqlIuybm5xBKqGv+voa1dGjbWP2+YMU/9SdLiiYjaz/S9LU6cIqA7Fxg7S7g+EXg7NV722zcA7w6U8Csn4B35xbd9sJHwCNDBTw/ScCqPwXU6GvAlB+LHvP3UQF1nhdQ81kBh84KaDRYwP39BSSlFt3f7V0BVXoLmPy9gGVbBTz8sgE/bb/3fClpAlb8LuBOlucEFL8KHzqdTvyFxcqHKXNdLsb5L9TCh7TLBbAcPqKiomTXQ/C0D22GDzm14zde2lxK7cwV5f05OTlmp9mXvq6M/waCIFh9j9pa+Xj55ZdNbjt16hSmT5+Of//9V3a7tEIi3f9rr72GLl26qLbD017HVKRtYyBEuKJ6XyP1Ii4AoNVDQN+2puHkbgGQaSZnp2UWVR/MuZMFhJr5OJm3tuj/y3+/9/+eYwWcTwLenSvAYBAw4ouifRcUAg0GCjh4BjhzBXjj86KunfV/Fz32vfkCnp0gYP9JoPf7Apr9x4CdhwU89Z6AZ8YLGPIpw4dmlKeC0j3mKh+WwofyC9tS+ChZsqTqnCCeQnksal+0ZMpa+Lh586asm6Jly5ay+9XCB2C9omJr+Fi7dq3JbUuXLsVbb72Fxx9/XHa7tDtGuv+RI0di9erVsonpjDztdUxFAgJ0qBbwncntURFAg5pAtQrqj2sSDzS+X2cyZuTtrwWM/sr8l3eahbdBoQEIsnApGJXeblF2blF4UbP/JHDTwoWl9xwHWr4mYOf/n0ewYpv5bd3N7z5dlaeC0j32hA9rlQ/pB3iJEiVkXy6ePuDU39l66qq1kHDz5k3Zl7pyoKi0wiKtjFl6fnNnttgyUFVKOfW/dF15+fSAgACsWLHC48cu0T1RQckmtw3rAYSH6fDrZNPqRpcEIDio6PbqZsKJOanp5u/LyAZuWwgnGTnmv4rvZAMlS6jfp9MBtyyED0/mt+GDlQ9T5rpdIiMjAdhW+ZBO9JSVlSX7AgkJCZF9UHvah7YySPk7W8OHtSCfmpqKs2fPiuvSycQA+yof5u5TttncqbfmWAofRsrXiae9jume0qFXgeyTRSs55zCg5W58OLAoXDxUUx4+gvTAonfv3Vbe/EWuVXV403K3y00L4eR2pvmv4oxsIMLC7yKGDy9h/KCwdmErf2Tuy8Y48E9tDIClykdmZqbs7+zp4YOVDzlzrwflQExr76WsrCzxirAAULduXdn90teVo+FDebv0GkS2sCV8KK9o6mmvY7qnZYtHgUMtgcOPQfdPHYwdWA56vfpg083TdSgdde++mJLFu+jlpWvm7xu3QMDmfebvT7cQPu5kAXlmfivrdMAt8xcNV5V/1zPGffhd+GDlwzxzXzbG02+V028DpmewKLtdLIUPLa9oq4bho2iGW6NHHnlEdZt27dph9OjR4rr031jtDJXs7GwcO3ZMXH/wQXlnuvR1Z2u3i62VD+nkYLZciVQtfAQEBJg9owtg+PBko0ePxpaNK/D9F4Nx8sRx1Kghv+TtD+8VfQZVqwA0ryd/bLgTPw7OqI97FVmrfFga11HcykeG+rhvt/OsTnc3MJZ4WfkwZe5vojwdUWrcuHGydUvhIzQ0FKVLlxbXbZlC250YPoA5c+YgMjIS999/P5o1a2Z2O2lXifTfWK2bIzs7G6dOnRIfV716ddn9aWlp4rKtlQ9zZ84oHyPdd/v27bFo0SKz+wTkg2eN+woLC5MFZXa7eI+AgAC0bWt+Uo/nOuiQULeoiyVIUREpYWaan7aNiwasTl9u/nkrlwMuX7e9nTczzI9GvZNtPmDYM+YjIxsoHWV9O1fz28oHB5yaMvcLtE+fPqrb79q1C48++qjsNmX4UI75kA42NH4heQqGD6BMmTJYsGCBrLKhxlz4UHtfZWdni9dCKVu2rEkFTfoaccaYj++++w5vvPEGUlNTZZWPChWsjyBUq3xYOqML4CnZ3q76fTqUCDWtwj5a13TbpR/osGVmAN542nzV9v2XgPjKZu9GA5UJzEbNizW7/fx1AlLS1O9LzwR2Hy9eN8odVj60wcqHedIvgXfffRfZ2dmIiYkxO7+B2vTW1rpd1B7jKfxtRlNHmAsfat2ZBQUF4qm2UVFFP7lWr16N7t27Q6/Xy+bhkIZeW8NHqVKlcOvWLQDAkSNHMGPGDABFE4Y999xzsu2sycrKgsFgQEBAgNnwwcqHf6hfQ4dZw4vm0gCAcS8Cz/z/mdnlS6s/ZutMHR5vrEOPMernzpYrBcz5rw4Jw2wPDMY5PNSkpgM//2HzrgCw20Uzxl8pBoMBhYWFquMY/JU0fERHR+P999832SY8PFy86Jfxi0R5v5Fa+GjRooW43rixmWkENcLXgu2KU/kA7nXHREdHAwC6du2KP//8E2XLlpVdAVf6RW/rmI+YmBgxfGzbdm8ig3Xr1mHdunWy7Wxx/vx51KxZ0+bKB8OH7xr+tA7Dn9ZBEARZ11tRF41pgHi8cdE2YSq/Y4Z2Az54SedQl8djDYFt/1rfzpJhMwRsnApUiNV2zJ3fdbuY+9AkmAQFNRs2bECfPn2wePFi1fuVXx7KfT7yyCMYNWoUmjRpgrlz5zqp5c4RG3uv9FmnTh0NW+L5pK8PaeCw1p1pDB86nQ4tWrQwuV6QLd0ut27dwsGDB8V1aahQzlgqpTzF15xatWqhefPm4ngRVj7IlsHxv392bxu18PHxUB0qxOrEeUTMqVjG/H392zseGA6fgzhjqpb8Lnzw4nLmmRvzIdWyZUssXbrUZKyHkfRLSRk+jPv89NNPsW/fPjRq1MgZzXaa8PBw/PrrrxgyZAhWrVqldXM8mvR9ZK3bRUqtWiZlrdslPT0dNWrUwKhRo8TbqlatanZ/JUuWRLNmzfDWW2+ZDDz8+OOPMW/ePPz000944oknZPft2rVLXGblg9QMlvRGn16sw2ON7gWDEb3lIWH9JzrZqbtdE9T3+f1YHepUUb+vVCTwdBvz7Xmlh/pYk9d7md62YhuQnattAPG7bhdWPsyzJXxYI31cXl6eyYBTT9ejRw/06NEDBoPB5PLqdE9xu12MjJUPc6Rf9JMnT0afPn1klY29e/fKzmABgLZt26Jy5criWA+phIQEbNy4UfW5mjVrhjZt2gAA3njjDbNtUh4TKx8EANOG6dD0gaJrwdSqJA8b9WvosGEqcOM20K8dTOYW+fYdHcYtELBgPfBkM+DjFy8jJrYyypfW4dEHgVr97gWDHi2Bzo/q0LQOEBWhwxtPF12Qzqhbc8AgAONe0GFYD6DeS/ce2/lRYNJgHdb/XXStGKkt+4FuLaAZvwsfrHyYZ0u3izXKLyXjPvV6Pa+V4kOKM+BUqjjhIzExEePGjcPs2bPF24xjO4zKlSuHrl27Ii4uDj///LNJYLT0fNLTvvv27Yvp06erbnf9uvycSVY+CCgKAoPVx+IDAJ5oar6LJDZah6/e1OGrN/H/P3QElP3/jF2zog7pG4rCwYVkYFhPICzk3r4+Gx6AEb0FzFsnoH0THdo0vHdfhVggbysw5FMBSTeLQk5kuA7bZwE1nhVwV3Im/KqdArq10G7ch9+FD1Y+zEtOvncdBHsrH+a6Xbyh6kG2s7fyYa3bpWXLlggKChJDzPHjx2X3S8PH+PHj8e6774o/KGJjY4sVPoyXDQCAESNG4NixY6pVkmvX5FNXKsMGX9vkbJHhOjzV2vz9VSvoMHmIenAIDtLhu7Hy+yqV0+Hc0qLJylq8JiArB1j7F1BYKCAwUJsA4nc/RVn5UPfpp5/i888/F9ed1e3C8OGbXNXtUrp0adlF6JSTiUnDR8OGDWXvZ+mAYXPPN3DgQABFr1PpWTYVK1bEhg0bMGXKFJN9KCfZk87qW6lSJbvfK0TuVKmcDg1q6fDE/09cHKQHLlqYEt7VWPkgAMDbb78tW7c3LCgHIhrHfPAD2rfYMuA0MDDQ5IvbWuXDuE1YWBhycnJMwodxsjLAdN4OtfChHJ8xbdo0NG7cGK1atVLtLilZsqTJbcrn6dSpE1q0aIG7d+9i5cqVVo+HyJOMeU6HUc8CD8cDAQHsdnEbVj5sY28/tk6nQ3BwMPLz89nt4sNsOdU2KirKZIxGrVoq0zuqMBc+pPuTjtkA1MOHcu6WmJgYDBs2zOzzSq/KbLR06VLZenR0NP7880/zjSfyYI3u94xravld+GDlw5TaxcAcGUQXGhqK/Px8drv4MFu6XaKjo2VhISwsDPXqKa7eZUaJEiVw69Yt5OTkoKCgAMePH4cgCOJMqYBpRUI5EBRAsQc5Kysfv/32Gzp06FCsfRCRdX4XPlj5MGWcsVTKkfAhncKe4cM32XK2S2xsLM6fPy+uN2nSBHq9bR85xu6SrKwsdO3aVXUgqHLG0rp1TS/GUdxZa5WVD+UkaETkHMX6WbBs2TJ07NgRgwcPll2wyZz09HS0a9fO7sa5AisfppSlcQA2f0moMf6Nc3JyxL8xx3z4FlsqH507dxan0I+KirJ6sTop4ym36enpqsEjPDzc5IJuPXv2xLvvviu7rbhVC2Xlo1y5csV6PBHZxubwcfLkSSxZsgTLly9H3759MWfOHKuP+eKLL0wmBNIaKx+mpIP4jBztdgHklydn5cO32DLgNDo6Gvv27UNOTg5u3rxp9gKFapQDRZXUxmaEhobio48+Qnp6OsaOHYvp06ejfv36Nj8nYBo+1J6HiBxnc/jYsWMHunbtiujoaLRt2xaHDx+2uP2RI0dw7tw5j/vlwMqHKbXKhzO6XRg+fJctlY/g4GDodDqEhoYWu/vDWviwdBn7yMhIfPjhh+jZs2exnhNg2CByF5tr6ykpKUhIKJqQXqfTQa/XIycnx+S6B0DRefFTp07Fe++9hzfffNPifvPz800qEHq93uKHiyOkX6q5ubkwGNQvfWwv4/6cvV9X+eabb1RH/wcGBpo9BmvHqBY0goODveZvAnjfv6M9HDlG6fvoypUr+OWXXwAAe/bsEW+39BqyRu1zRcra68neY1N2D3ryvz9fo77B147R1kHeNocPg8Eg+1UQGhqKzMxM1Q+JFStWoHHjxjYN1lq4cCHmzZsnu613797o06ePrU0rloyMDHE5OTnZZdfvSExMdMl+nenEiRNmTztMTk62eElzwPwxql0BMigoyCuvleIN/46OsucYpdWOQ4cOoVcv06tXZWRk2P1vrnYGlpROp7Np38U9NkEQULt2bZw+fRqvvvqqV7xm+Rr1Db5yjNWqVbNpO5vDR0REhOysiLy8PNUvmdTUVKxZswYLFy60ab8DBgxA//795Y1yYeWjQoUK4nLJkiVRpYqZSwjayWAwIDExEZUqVfL4a5lIL0uuVL16ddn001LWjlHtcfHx8U7/W7uSN/072suRYxQEAXXq1MGJEyfMbvPYY4/Z/W+uNmeHVHh4uMV9O3Jse/bswaFDh5CQkFDs7iJ34mvUN/jDMaqxOXzEx8fj6NGjaNOmDfLy8pCcnKw6VfK+fftw7do1dO/eHQBw+/ZtdOzYEcuWLTM5NQ4oKp+6KmiokVZq8vPzXfaPHRAQ4PEvJEsDbkNCQqy239wxqp3Z4q1vLG/4d3SUvce4ceNG/PLLL6pjp5o1a4aGDRva3Sa1OTukgoODbWqzPccWHR2N1q0tXFjDw/A16hv84RilbA4fzZs3x+zZs9GgQQPs2rULjRo1Uj0ds1OnTujUqZO43rVrV6xdu9Y5rXUCnu1yj6VuFWecaitVsWJFu/dHnqly5coYMWKES/btyIBTIvJ8NsesyMhITJw4EfPnz0dSUhJGjx6NzZs3Y9q0aa5sn9PxbJd7pOFDOXaH4YO0ZMuAUyLyXsX6hmnUqBEWLVokrnfo0MHqJD6eVPUAWPmQkoaPkiVLIicnR1xXG89jK7VuF4YPKg5WPoh8m/90MP0/Vj7ukYYPZ85voKx8PPDAA7LLkBNZowwfygGoDB9E3s3vwgcrH/dIw5fapcTtVblyZdn6gAEDnLZv8g/KM6aUkxUyfBB5N7+7sBwrH/cou12c5ZVXXsHNmzdx/vx51K5dG8OHD3favsk/KF+PZcuWxbFjx8R1hg8i7+Z34YOVj3tc1e1SqlQpzJgxw2n7I//DygeRb/O7bhdWPu5xVfggcpRa5UOK4YPIu/ld+GDl4x5XdbsQOcpa+HDkwodEpD2/Cx+sfNzDygd5Kna7EPk2vwsfrHzcw8oHeSrl65Hhg8i3+F34YOXjHoYP8lTKSpxykjqGDyLv5nfhg5WPe9jtQp5KOb1/+fLlZesMH0Teze/CR0BAgPjBxsoHwwd5B+UYEIYPIu/md+EDuPfB5e+VD2P4CgoKQmBgoMatITJPOd06wweRd/PL8GEc98HKR1HlQ+1CcERa69WrFwCgfv36Jhc65Km2RN7N72Y4BVj5MDKGD+WF4Ig8wdy5c9G5c2e0b9/e5D5/f+8SeTu/DB+sfBRh5YM8WalSpcxelDA7O9vNrSEiZ/LLbhdWPoowfJC3Yvgg8m5+GT5Y+SjC8EHeiuGDyLv5Zfhg5QMQBIHhg7xKz549xeW6detq2BIicpRfj/m4e/cuDAYDjh8/jiVLluCll15C7dq1NW6dexQUFMBgMABg+CDv8NVXX+H27duIjY3FSy+9pHVziMgBfhk+pHMEnD59Gs2bN8edO3fw+++/Y/fu3Rq2zH2kE4yFhoZCEAQNW0NkXbly5bBt2zatm0FETuCX3S7SU0vnzZuHO3fuAAD27NmDW7duadUst1KGj/r164vrLVq00KJJRETkJ/wyfEgrH0lJSbL7du3a5e7maEI62DY0NBQNGjTAJ598gt69e2Px4sUatoyIiHyd33e7LFu2THbfkSNH0KVLF3c3ye2UlQ8AGD16tFbNISIiP+KXlQ/ldSKk/OUUPmn44AynRETkTn4ZPgYPHmz2vpycHDe2RDtqlQ8iIiJ38Mvw0aZNG7PVD+mXsi9j+CAiIq34ZfgAgLCwMNXbWfkgIiJyLb8NH+a+cBk+iIiIXMtvwwcrHwwfRESkDb8NH6x8MHwQEZE2GD4UGD6IiIhcy2/Dh7luF38520U5wykREZG7+G348PfKx6hRo8Rlhg8iInInhg8FfwgfSUlJsuPkDKdERORODB8K/hA+bt68KVvX6/3yEj9ERKQRvw0f/nyqrXS8BwAkJCRo1BIiIvJHfhs+zFU+/GHAqfQYBw0ahKioKA1bQ0RE/obhQyEnJweCILi5Ne4lDR8VKlTQsCVEROSPGD4UBEFAfn6+m1vjXpzjg4iItOS34cPcmA/A98d9MHwQEZGW/DZ8WPrSvXXrlhtb4n7S8MHTbImIyN0YPlQcPXrUjS1xP1Y+iIhIS34bPsqVKydbj4uLE5f79OmDCxcuuLtJbsPwQUREWvLb8NGjRw+89NJLqF+/Prp27Yr58+eL9+Xl5eHpp5/WsHWuxfBBRERa8tupLcPCwrBw4UJx3WAwoGHDhvj3338BAMePH9eqaS7H8EFERFry28qHUkBAAHbt2iWu3717V8PWuBbDBxERaYnhQyI0NBSPPvooAKCwsNBnJxtj+CAiIi0xfCgEBQWJy75a/WD4ICIiLTF8KEjDh6/OdMrwQUREWmL4UGDlg4iIyLUYPhQYPoiIiFyL4UOB4YOIiMi1GD4UGD6IiIhcy28nGTPHF8OHIAjYvHkzYmJikJ+fj61btwIomtuE4YOIiNyN4UPBF8PHmjVr0KNHD5PbH3/8cej1fAkQEZF7sdtFwRfDx8iRI4t1OxERkSsxfCj4YvgoUaKEyW0///wzOnXqpEFriIjI3xUrfCxbtgwdO3bE4MGDcfv2bbPbHTt2DE899RSaNm2KMWPGoKCgwOGGuosvho+4uDjZemBgIHr27KlRa4iIyN/ZHD5OnjyJJUuWYPny5ejbty/mzJmjup0gCJg4cSKGDx+OrVu34sqVK9iyZYvTGuxqvhg+ypYtK1svVaoUdDqdRq0hIiJ/Z3P42LFjB7p27Yro6Gi0bdsWhw8fVt0uLy8Pw4YNQ5s2bRAREYEGDRogNTXVaQ12NV8MH8rKU0xMjEYtISIiKsbZLikpKUhISAAA6HQ66PV65OTkICwsTLZdaGgoWrVqJa7v378fo0ePNrvf/Px8k2uo6PV6BAcH29o0p5Ke/ZGXlweDwVCsxxu3L+7jXCkrK0u2bjAYHGqfJx6js/EYvZsvH5sRj9E3+NoxBgTYVtOwOXwYDAZERESI66GhocjMzDQJH1JbtmxBSEgIGjRoYHabhQsXYt68ebLbevfujT59+tjaNKeSflEnJSXh0qVLdu0nMTHRWU1ymHJ8zs2bN+0+LilPOkZX4TF6N18+NiMeo2/wlWOsVq2aTdvZHD4iIiJkX8x5eXkWxw2kp6fjs88+w7Rp0yzud8CAAejfv7+8URpWPsqUKSMuR0dHo0qVKsV6vMFgQGJiIipVqmRzAnS3tLS0Yh+XlDcco6N4jN7Nl4/NiMfoG/zhGNXYHD7i4+Nx9OhRtGnTBnl5eUhOTkZ0dLTqtoIg4MMPP0SPHj0QHx9vcb/BwcGaBQ010rYUFhba/WIICAjwmBdSTk6ObP2+++5zSts86Rhdhcfo3Xz52Ix4jL7BH45RyuYjbd68OTZs2ICdO3di1qxZaNSokdnZMRcuXIjs7GwMHDjQaQ11F+mA0759+6JGjRq4fPmyhi1ynDR86HQ6fPvttxq2hoiI/J3N4SMyMhITJ07E/PnzkZSUhNGjR2Pz5s2q3So//PADTpw4gU6dOqFjx474/PPPndpoV5KGDwA4f/68SbeQt8nOzgYAhISE4MKFC+jQoYPGLSIiIn9WrAt7NGrUCIsWLRLXO3TooPpFtm3bNocbphVl+ACAnTt3olOnTlizZo3q/Z5q2rRpmDx5MtLS0gAUzffhyFgPIiIiZ/CfDiYbmQsXGzduFK8G6w0EQcAHH3wgBg/AdOwHERGRFhg+FCxVNm7evOnGljjm9u3bYneLkTdN9kZERL6L4UPBUvjIyMhwY0scc/36da2bQEREpIrhQ8FS+Lhz544bW+KYa9euad0EIiIiVQwfCpbCx9ixY1G7dm2sW7fOjS2yDysfRETkqRg+FCyFj4KCApw5cwbPPPOMG1tkH7XKx7BhwzRoCRERkVyxTrX1B7acSqscyOmJpJWP999/HyEhIRg6dKiGLSIiIirC8KGgDB9BQUG4e/euRq2xz+HDhzFlyhRx/fnnn0fNmjU1bBEREdE97HZRCAkJka1XqlSpWI+/evUqJk2ahH79+qF+/fqoWrUqDh06pLrta6+9hgYNGuDgwYP2NlfV4MGDxeWqVauiRo0aTt0/ERGRI1j5UFBeLK9SpUo4f/687LaAgAAIgqB6Vd8PP/zQ5NopCxcuxGeffSa77dChQ/jyyy8BFM0Ue+PGDccbj6LJxfbt2yeu9+7d2+LVh4mIiNyNlQ+FmJgY2XpsbKzJNgaDwey4j7Nnz5rcphYspLelpKQUt5lmSWc0BYBx48Y5bd9ERETOwPChEBkZKVtXVkKMdu7ciatXr5rcrjYXiNrMoqGhofY10IoLFy6Iy4MGDULJkiVd8jxERET2YvhQ0OvlPVHR0dGqF2N74oknULt2bZOqRXp6OoCiCkpgYCAA9WnZ8/LynNVk0eHDh/H++++L69WqVXP6cxARETmK4cOK6OhorFy5EgMHDkS9evVk92VnZ+PHH3+U3WasfERHR6N06dIA1Csfzjxd99atW+jbty8eeughrF+/Xryd4YOIiDwRw4cVMTExePjhh7FgwQI8+eSTVrc3Vj4iIyPF8SJqlQ/lFWYdCSNfffUVli9fLrstPj4eTzzxhN37JCIichWGDyukYzPUxk8UFBSIy7m5ucjPzwcAREVFiZWPrKws5Obmyh6nDB+OXHFWOptp69atsWzZMuzfvx+lSpWye59ERESuwlNtrRAEQVxWCx9TpkzBsmXLoNPp0L9/f9m20gnLUlJSUKlSJUyaNAkXL1406RJJTU1F5cqV7WqjdPzIrFmz8NBDD9m1HyIiIndg+LBCOkdG9erVTe6/desWbt26BQA4cOCAeHtUVJTszJnvvvsOCQkJZk99vXz5Mho1amRXG6XhQzlJGhERkadht4uKOXPmAADCw8PRs2dP8fZOnTph/PjxePjhh63uIyoqCs8//7y4vnLlSvzxxx9mtz958iRycnJklRZbMXwQEZE3YfhQMXjwYPzyyy/YvXu3bNxEYGAgPvjgA/z1119W9xEZGYmEhARxevYrV65YvGjdu+++ixIlSqB+/fomE4VZw/BBRETehOFDRVBQEHr27Im6deuavV85E6pSVFQUgHvXhrl165ZNF6g7evQoli5dWqz2MnwQEZE3Yfiwk7UzSYxnusTFxYm3JSUl2bTvv//+u1htYfggIiJvwvBhJ3PTrhuVKVMGAHDfffeJt506dUp12/vuuw/vvvuuuM7wQUREvoxnu9jJWvgoW7YsAHnl488//1TddteuXahSpQq2bt2KvXv34uzZs8jKykJ4eLhNbTGGD51OZzI9PBERkadh5cNOxjEdRsrZT43ho2bNmlb3FRYWBqBoVlIjtavjmmMMHyEhIbJTg4mIiDwRw4edlJWPqlWrytaN4aNr164YMmSIxX2VKFECAHD//feLtzVo0AAGg8GmtkjDBxERkadj+LCTtfAREREBoOgquXPnzjU7e2lAQIBY+ZCGDwA2ndILMHwQEZF3YfiwkzJ8SMd2ADDp/jAXPoYNG4bAwEAAMJnh9OTJkza1heGDiIi8CcOHnZThIyIiAu3btwcA9OrVy2R75am5t2/fRlpaGr744gvxtmrVqmHo0KHiurmzY5QYPoiIyJswfNhJGT5KlCiBVatW4ffff8fkyZNNtq9Xr564/NhjjyE6Otpk0CoAjB07Vlxm+CAiIl/E8GEntfBRokQJtG7dGsHBwSbbDx48GDVr1kSLFi2wfPlys/uNi4sTx4CcO3fOprYwfBARkTfhpBB2Ug4ONZ6xYk7VqlVx5swZCIJg8XTYgIAAlC9fHhcuXMD169ettqOwsBCFhYUAGD6IiMg7sPJhp1q1asnW1aodamyZh6NcuXIAbLseDGc3JSIib8PwYSedTocOHToAKAoeyrNdHGGcIwQAUlJSLG7L8EFERN6G4cMBP/zwA9566y2sWLFCdfCovYyVDwBWu142bdokLjN8EBGRN+CYDweULVsWU6dOdfp+peHjxo0bFrf973//Ky7fuXPH6W0hIiJyNlY+PJC026VPnz4oV64cmjdvjgsXLphse+3aNXG5uFfDJSIi0gLDhweqUqWKuHznzh3cuHEDu3btwoIFCyw+7s0333R104iIiBzG8OGBOnXqhP79+6NatWqygaypqamy7QRBQFBQkLgu7YIhIiLyVBzz4YGCgoLw448/AgDOnj0rntabmZkp2y43N1c8FbdNmzaIjY11b0OJiIjswMqHhwsPDxeXs7KyZPelpaWJy8oZV4mIiDwVw4eHi4iIEJeVlQ+GDyIi8kYMHx5OOm27pfDhzHlGiIiIXInhw8MFBgaKF5qTdrukp6cjPT1dXGflg4iIvAXDhxcwdr0YKx/vvPMOoqOj0alTJ3Ebhg8iIvIWDB9ewDjo1Fj5+OSTT0y2kU5MRkRE5MkYPryAsvKh1LhxY3Tv3t2dTSIiIrIb5/nwAsbKR3Z2NvLz803u37dvH3Q6nbubRUREZBdWPryA9HRbtavcMngQEZE3YfjwAtKJxpKSkjRsCRERkeMYPryAtPKRnJysYUuIiIgcx/DhBUqWLCkuX716VcOWEBEROY7hwwtI5/C4fPmy7L6KFSu6uTVERESOYfjwApbCx5IlS9zcGiIiIscwfHiBmJgYcXnfvn3i8sSJE9GyZUstmkRERGQ3hg8vIK18nDt3TlyuVauWBq0hIiJyDMOHFzB33RZeyZaIiLxRscLHsmXL0LFjRwwePBi3b982u11KSgoGDhyIjh074qeffnK4kf5O2u0i1bp1aze3hIiIyHE2h4+TJ09iyZIlWL58Ofr27Ys5c+aY3XbKlClo06YN1q1bh/Xr1+PatWtOaay/Uqt8LF68GGFhYe5vDBERkYNsDh87duxA165dER0djbZt2+Lw4cOq2929excHDhxA3759ERQUhI4dO2LXrl1Oa7A/Uqt8VKtWTYOWEBEROc7mC8ulpKQgISEBQNG1RPR6PXJyckx+faelpaFChQoIDg4GAJQvXx6HDh0yu9/8/HyTi6Xp9Xrx8d7GYDDI/u8M0knGjKpUqeLU5ygOVxyjp+ExejdfPjYjHqNv8LVjDAiwraZhc/gwGAyyab5DQ0ORmZlpEj6U24WFhZm9FDwALFy4EPPmzZPd1rt3b/Tp08fWpnmkxMREp+7vkUcewd69ewEAdevWRW5uLi5duuTU5yguZx+jJ+IxejdfPjYjHqNv8JVjtLUqb3P4iIiIQFZWlriel5enejVVW7czGjBgAPr37y9vlJdXPhITE1GpUiWbE6Attm3bhu3bt8NgMKB169ayi825m6uO0ZPwGL2bLx+bEY/RN/jDMaqxOXzEx8fj6NGjaNOmDfLy8pCcnKw6EDI8PBwFBQXIzMxEREQETp06hbJly5rdb3BwsNcGDUsCAgKc+kIqUaIEnnzySaftzxmcfYyeiMfo3Xz52Ix4jL7BH45RyuYjbd68OTZs2ICdO3di1qxZaNSoEfR69ezStm1bfPLJJ9izZw9+/vlntGrVymkNJiIiIu9mc/iIjIzExIkTMX/+fCQlJWH06NHYvHkzpk2bZrLtgAEDEBkZiRkzZmDIkCGoXbu2UxtNRERE3svmbhcAaNSoERYtWiSud+jQAR06dDDZLjg4GKNGjXK4cUREROR7/KeDiYiIiDwCwwcRERG5FcMHERERuRXDBxEREbkVwwcRERG5FcMHERERuRXDBxEREbkVwwcRERG5FcMHERERuRXDBxEREbkVwwcRERG5lU4QBEHrRhAREZH/YOWDiIiI3Irhg4iIiNyK4YOIiIjciuGDiIiI3Irhg4iIiNyK4YOIiIjciuGDiIiI3Irhg4iIiNyK4YOIiIjciuHDAa+//jqWLFmidTNcrmvXrkhKSrK6jbdZvHgx2rdvj65du2LPnj1aN8cpBEHAxx9/jObNm6Nz587YvXs3AODzzz9H+/bt8d///he5ubkAgCtXrqB///5o2rQphg0bhszMTADAsWPH8NRTT6Fp06YYM2YMCgoKNDseW/jL+xDge9GbOOO9ePfuXXzxxRcYMmQIvvrqK49/LxYHw4edCgoKcPDgQRw4cEDrppAdzp49i0WLFuHHH3/Ee++9h/fff9/iG3v//v04deqUG1ton02bNiE5ORnr16/HG2+8gU8//RTbt2/H/v37sXbtWjRq1AhLly4FAEyZMgVPPfUUtm/fjrCwMKxcuRKCIGDixIkYPnw4tm7diitXrmDLli0aH5V5fB96P74X1d+LAPDtt98iLy8P48aNw7Fjx7B+/XotD8mpGD7sdPz4cTRs2BAnT56EwWDQujlUTLt27UKzZs1Qrlw5NG3aFHq93uIH2oEDB3D69Gk3ttA+5cuXx3vvvYfo6GgkJCQgNTUVf/zxB/r06YPQ0FD07NkTf/75JwRBQPfu3dGrVy+EhYXh4YcfRkpKCvLy8jBs2DC0adMGERERaNCgAVJTU7U+LLP4PvR+fC+qvxcBoGTJknj99ddRuXJltGzZEleuXNH4qJxHr3UDvNX+/fvRpEkTFBQU4PTp01i2bBkKCwvxzz//ICYmBpMnT0aVKlWwf/9+rFu3DlWqVMHSpUuxYsUKREdHa938Yps7dy4aN24slnS7du2KtWvXatwq+yUnJ6NcuXLiepkyZZCcnIx169bh999/R0xMDCZMmIAqVaqge/fuyM7ORkBAAGbPno3p06ejbt26GrbevAYNGojL+/btQ926dXHjxg3UrFkTABAREYG0tDTodDq0b99e3Hbv3r1o164dQkND0apVK/H2/fv3Y/To0W5rf3H52/sQ4HvRX96LANCvXz8AECsoo0aNct8BuBgrH3Y6cOAAGjZsiIYNG2L//v0AgNzcXKxduxY9evTAtGnTxG13796NW7duYcmSJYiKitKqySSRm5uLoKAgcT0oKAgXL17E9evXsX79egwaNAgzZsxAaGgoNm3ahOeeew5vvfUWNm3a5LEfdlIFBQWYN28ennvuOQiCgIiICPG+wsJC2bZHjx7FmTNnZB+AALBlyxaEhITIPkQ9Dd+H3o/vxXvU3oupqakYPHgwQkJCEB8f77Z2uxrDhx0KCgpw5MgRvPnmm1i6dKn4odelSxcEBASgU6dOOHLkiLh9ZGQkRo4cidjYWOh0Oq2abbOLFy+Kx2QkbbcgCO5uktOFhoYiPz9fXM/Pz8fXX3+Nbt26Qa/Xo3379vjmm280bKFjfvzxR8TFxSEhIQHh4eHIysoS75Me9927dzF58mSMGjVK9gWQnp6Ozz77DG+//bZb210cvv4+BPhe5HsRiI2Nxdq1a1GxYkV8//33bm27KzF82OHo0aOoU6cONm/ejN9++w2HDx9GYWGh+EEgCAICAu79aR944AGv+bADigaA/frrr+J6fn6+LK3fuHFDi2Y5VVxcHK5fvy6up6SkoHHjxuJ6YWEhfv75Zy2a5rCjR4/ip59+wpgxYwAA8fHxOHr0KADg2rVrCAkJEbedNWsWHnjgAVlXiyAI+PDDD9GjRw+P/qXl6+9DgO9FwL/fi9u3bwcABAQEoHXr1rh48aLb2u5qDB922L9/Px544AEARam9XLlySE9Px7p162AwGPDbb7+hfv36GrfSfrVq1cKxY8eQlZWFU6dOoUSJEihXrpz4AbF8+XKNW+i4hIQE/P3337h27Rp2794Ng8GAxx57DOvWrUNBQQH27duHVatWidtHRUWJx5+WlqZNo22QlpaGt99+G++//z5iYmIAAO3atcP333+Pffv2YebMmWjdujUAYOPGjdi7d69JP/LChQuRnZ2NgQMHur39xeHr70OA70V/fy8uWbIEGzduhCAI+P333/Hggw+6/ThchQNO7fDPP/+gZ8+e4vqDDz6IDRs2oEOHDujatStKlSqFjz76SMMWOqZKlSp46qmn0Lt3b4SGhmLs2LGoVKkSRo4ciYMHD6JZs2ZaN9Fh1atXx+DBg/H8888jJCQEH374IRo1aoSLFy+iS5cuKF26ND744ANx+yeeeAIjR47E0qVL8dRTT+HVV1/VsPXmbdiwAampqRg3bpx427JlyzB8+HB89tlnqFatGoYMGQIA+P7773Ht2jV0794dANCkSRNMnjwZP/zwAwRBQKdOnQAAnTt3xvDhw91/MFb4+vsQ4HvR39+LY8aMwfvvv4+ZM2eiZcuWePrppzU5FlfQCb7QaegBxo8fjy5duqBJkyZaN4XIb/F9SOQd2O1CREREbsXKBxEREbkVKx9ERETkVgwfRERE5FYMH0RERORWDB9ERETkVgwfRERE5FYMH0TkNElJSZxjg4isYvggIk28/PLLXn0peCKyH8MHERERuRXDBxE55M8//0SPHj3Qtm1brF+/Xrz94MGD6NevH5o3b44XXngB58+fBwB89NFHaNKkCf755x9MmDABTZo0kV2D5dixY3jxxRfRunVrjBo1CpmZmW4/JiJyLYYPIrLbzZs38e677+LFF1/EokWL8OeffwIADAYD3n77bTz++ONYvXo1GjVqhM8++wwAMHLkSGzbtg0PPfQQ3n77bWzbtg0jR44EAGRkZGD48OFISEjAsmXLkJWVhZkzZ2p1eETkIgwfRGS3v//+G/fddx969uyJSpUq4eWXXxbvW7x4MV544QVcv34dGRkZuHTpEgAgNDQUJUuWRGBgoLgcGhoKANi5cyf0ej1efvllVKhQAc899xx27NihybERkevotW4AEXmv1NRUlC9fXlyvWLEiACAgIABLlizB6tWrERcXh3LlysFgMFjd3/Xr15GWlobHHnsMACAIArKyspCXl4eQkBDXHAQRuR3DBxHZLSYmBqmpqeL6tWvXAAD79+/H6tWrsXLlSpQqVQo7d+7EyZMnZY8NCAiA8rqW5cqVQ3x8PD7++GMAReEjMzMTej0/qoh8CbtdiMhuzZo1w8WLF7Fu3TpcuXIFc+fOBQBkZ2cDKBrDcfDgQcycOdMkaFSsWBH79u1Damoq9uzZg8LCQrRo0QLXrl3DsWPHEBISgq1bt2L48OEmjyUi76YT+K4mIgds3boVn3/+OXJzc/Hkk0/ihx9+wO7duzF+/Hj88ccfuO+++9C1a1d88cUX+O2331C6dGkAQHJyMsaOHYvjx4+jfPny+Omnn6DX63Hs2DF8+umnOHfuHKpXr47Ro0ejbt26Gh8lETkTwwcRERG5FbtdiIiIyK0YPoiIiMitGD6IiIjIrRg+iIiIyK0YPoiIiMitGD6IiIjIrRg+iIiIyK0YPoiIiMitGD6IiIjIrRg+iIiIyK3+DzTL75wiVdGyAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pred = model.predict(n=len(val_stock), series=train_stock)\n",
    "print(\"model {} obtains MAPE: {:.2f}%\".format(model, mape(pred,val_stock)))\n",
    "stock_scaled.plot(label='actual')\n",
    "pred.plot(label='forecast')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "d1fae330",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GPU available: True (cuda), used: True\n",
      "TPU available: False, using: 0 TPU cores\n",
      "IPU available: False, using: 0 IPUs\n",
      "HPU available: False, using: 0 HPUs\n",
      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "181be240d4d849db8e6bc10a663b4d41",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Predicting: |          | 0/? [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAPE = 5.83%\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "historical_fcast_theta = model.historical_forecasts(\n",
    "    stock_scaled, start=0.6, forecast_horizon=3, verbose=True, retrain=False\n",
    ")\n",
    "\n",
    "stock_scaled.plot(label=\"data\")\n",
    "historical_fcast_theta.plot(label=\"forecast-non-retrain\")\n",
    "print(\"MAPE = {:.2f}%\".format(mape(historical_fcast_theta, stock_scaled)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "9c1079f3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model_es = ExponentialSmoothing()\n",
    "model_es.fit(train_stock)\n",
    "probabilistic_forecast = model_es.predict(len(val_stock), num_samples=200)\n",
    "\n",
    "stock_scaled.plot(label=\"actual\")\n",
    "probabilistic_forecast.plot(label=\"probabilistic forecast\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ffb46c7a",
   "metadata": {},
   "source": [
    "## 模型的参数与分类\n",
    "\n",
    "https://unit8co.github.io/darts/generated_api/darts.models.forecasting.nbeats.html#darts.models.forecasting.nbeats.NBEATSModel.save\n",
    "\n",
    "Darts库提供了一系列丰富的时间序列预测模型，这些模型大致可以分为以下几类：\n",
    "\n",
    "* 统计和经典方法\n",
    "1. **ARIMA** (`ARIMA`)：自动回归积分滑动平均模型，用于处理线性趋势和周期性。\n",
    "   - 参数包括`p`（自回归项）、`d`（差分次数）、`q`（滑动平均项）等。\n",
    "\n",
    "2. **ExponentialSmoothing** (`ExponentialSmoothing`)：指数平滑法，适用于具有趋势和季节性的序列。\n",
    "   - 参数有平滑类型（如`'simple'`, `'holt'`, `'winter'`）、平滑参数等。\n",
    "\n",
    "* 深度学习模型\n",
    "1. **NBEATS** (`NBEATSModel`)：神经基函数展开分析模型，擅长捕捉多种频率的周期性。\n",
    "   - 参数包括`input_chunk_length`、`output_chunk_length`、是否使用堆叠层（`generic_architecture`）等。\n",
    "\n",
    "2. **RNNModel** (`RNNModel`)：基于循环神经网络的模型，如LSTM或GRU。\n",
    "   - 参数涵盖单元类型、层数、隐藏层大小、是否使用双向结构等。\n",
    "\n",
    "3. **TCNModel** (`TCNModel`)：时间卷积网络模型，适合长序列预测。\n",
    "   - 参数包括卷积核大小、层数、 dilation_base等。\n",
    "\n",
    "4. **TransformerModel** (`TransformerModel`)：基于自注意力机制的模型，适用于复杂序列模式。\n",
    "   - 参数涉及头数、层深、隐藏尺寸等。\n",
    "\n",
    "* 混合模型\n",
    "1. **RegressionModel** (`RegressionModel`)：可包装Scikit-learn或其他回归模型，灵活适应多种回归策略。\n",
    "   - 参数包括内部回归模型的选择、是否进行概率预测等。\n",
    "\n",
    "* 高级模型与集成方法\n",
    "1. **EnsembleModel** (`EnsembleModel`)：模型集成，可以组合多个基础模型的预测。\n",
    "   - 参数主要是组合的模型列表。\n",
    "\n",
    "2. **Theta** (`Theta`)：Theta方法，专为季节性时间序列设计。\n",
    "   - 参数相对较少，主要涉及季节性周期。\n",
    "\n",
    "* 预测后处理\n",
    "1. **ProbabilisticForecast`接口的模型：如`QuantileRegression`，提供概率预测能力。\n",
    "\n",
    "* 特殊用途模型\n",
    "1. **ProphetModel** (`ProphetModel`)：Facebook开源的Prophet模型的封装，适合具有强季节性和趋势的时间序列。\n",
    "   - 参数包括节假日效应、季节性模式等。\n",
    "\n",
    "* 自定义模型\n",
    "Darts也支持自定义模型，用户可以根据需求实现自己的模型类，继承自基本的模型接口。\n",
    "\n",
    "* 参数差异\n",
    "1. **输入输出长度**：大多数模型都有`input_chunk_length`和`output_chunk_length`参数，分别控制模型观察过去的序列长度和预测未来的序列长度。\n",
    "2. **模型复杂度**：深度学习模型通常有更多的参数来调整网络结构，如层数、节点数、卷积核大小等。\n",
    "3. **协变量支持**：某些模型支持额外的协变量输入，如`add_encoders`参数，允许模型利用外部信息。\n",
    "4. **预测类型**：部分模型支持概率预测，需要指定似然函数等参数。\n",
    "\n",
    "总体而言，Darts模型的多样性允许用户针对不同时间序列特性和预测需求选择最合适的模型，并通过调整参数来优化预测性能。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2622cbf6",
   "metadata": {},
   "source": [
    "## 模型参数\n",
    "\n",
    "神经基函数展开分析时间序列预测（N-BEATS）\n",
    "\n",
    "参数：\n",
    "- input_chunk_length（int）：作为模型输入的时间步数（每块）。应用于目标序列，以及过去和/或未来的协变量（如果模型支持）。\n",
    "\n",
    "- output_chunk_length（int）：内部模型一次预测的时间步数（每块）。同时也是作为模型输入使用的未来协变量的未来值数量（如果模型支持未来协变量）。这与predict()中使用的预测期n不相同，n是使用一次性或自回归预测生成的所需预测点数。设置n <= output_chunk_length可以防止自回归。当协变量没有延伸到足够远的未来时，或者为了禁止模型在预测时使用过去和/或未来协变量的未来值（取决于模型的协变量支持）时，这一点很有用。\n",
    "\n",
    "- output_chunk_shift（int，可选）：如有需要，可以在输入块结束后的未来方向上，将输出块的起始点移动的步数。这将在输入和输出之间创建一个间隙。如果模型支持future_covariates，则从移动后的输出块中提取未来值。预测将从目标序列结束后的output_chunk_shift步开始。如果设置了output_chunk_shift，模型无法生成自回归预测（n > output_chunk_length）。\n",
    "\n",
    "- likelihood (可选[str]) – 可以设置为'quantile'或'poisson'。如果设置了此参数，模型将成为概率模型，允许在预测时进行抽样。这将覆盖任何目标函数参数。\n",
    "\n",
    "LGBM 模型\n",
    "\n",
    "参数\n",
    "- lags (Union[int, List[int], Dict[str, Union[int, List[int]]], None]) – 用于预测下一时间步或时间步序列的滞后目标序列值。如果是一个整数，必须大于0。使用最后n=lags个过去的时间滞后值；例如（-1, -2, …, -lags），其中0对应于每个样本的第一个预测时间步。如果output_chunk_shift > 0，则滞后-1转换为在第一个预测步之前的-1-output_chunk_shift步。如果是一个整数列表，每个值必须小于0。仅使用指定的值作为滞后。如果是一个字典，键对应于序列组件名称（当使用多个序列时为第一个序列的），值则对应于组件的滞后（整数或整数列表）。键'default_lags'可以用来为未指定的组件提供默认的滞后值。如果某些组件缺失且未提供'default_lags'键，将引发错误。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "6756c3b0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "model ExponentialSmoothing() obtains MAPE: 11.03%\n",
      "model TBATS() obtains MAPE: 11.15%\n",
      "model AutoARIMA() obtains MAPE: 10.87%\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "AutoARIMA(add_encoders=None)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def eval_model(model):\n",
    "    model.fit(train_stock)\n",
    "    forecast = model.predict(len(val_stock))\n",
    "    print(\"model {} obtains MAPE: {:.2f}%\".format(model, mape(val_stock, forecast)))\n",
    "    return model\n",
    "\n",
    "\n",
    "eval_model(ExponentialSmoothing())\n",
    "eval_model(TBATS())\n",
    "eval_model(AutoARIMA())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "26fecb4e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#rnn_model=eval_model(RNNModel(input_chunk_length=24, output_chunk_length=12, n_epochs=50, random_state=0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4b6d8b38",
   "metadata": {},
   "outputs": [],
   "source": [
    "#eval_model(NBEATSModel(input_chunk_length=24, output_chunk_length=12, n_epochs=50, random_state=0))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77c6c8d0",
   "metadata": {},
   "source": [
    "## 多变量时间序列的股价预测\n",
    "\n",
    "**单变量时间序列预测** 侧重于使用单一时间序列变量的过去值来预测其未来值。预测模型依赖于该单一变量的历史数据来识别可以用来进行未来预测的模式、趋势和周期。例如，仅根据过去的温度记录来预测明天的温度。\n",
    "\n",
    "**多变量时间序列预测** 涉及基于历史数据预测多个相关时间序列变量的未来值。在这种情况下，预测模型会考虑多个变量之间的相互依赖性和交互作用来进行预测。例如，预测产品的未来销售量可能不仅考虑过去的销售情况，还可能考虑市场支出、季节趋势和竞争对手的价格等相关因素。\n",
    "\n",
    "**时间序列频率** 指的是时间序列中数据点的记录或观察间隔，代表了数据随时间的规律性和粒度。这种频率可以从高频数据（如金融市场中的分钟级交易）到低频数据（如年度经济指标）不等。不同的频率可以捕捉到各种趋势、模式和季节性。例如日常销售数据可能揭示出月度汇总中看不到的模式，如每周周期或特定日的影响。\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "2509de8f",
   "metadata": {},
   "outputs": [],
   "source": [
    "stock_ml[\"date\"]=stock_ml[\"date\"].astype(\"str\").astype(\"datetime64[ns]\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "852c8042",
   "metadata": {},
   "outputs": [],
   "source": [
    "def darts_series(stock_id,tz):\n",
    "    stock=stock_ml[stock_ml[\"股票代码\"]==stock_id][[\"date\",tz]].copy()\n",
    "\n",
    "    start0 = stock[\"date\"].min().date()\n",
    "    end0   = stock[\"date\"].max().date()\n",
    "    dates0=[]\n",
    "    print((end0-start0).days)\n",
    "    for i in range(1,(end0-start0).days):\n",
    "        dates0+=[(start0+timedelta(i)).strftime('%Y-%m-%d') ]\n",
    "    data3=pd.DataFrame(columns=['date'],data = dates0)\n",
    "    data3['date']=pd.to_datetime(data3['date'])\n",
    "\n",
    "    data3=data3.merge(stock,how='left',on='date')\n",
    "    data3=data3.ffill()\n",
    "    \n",
    "    series_stock=TimeSeries.from_dataframe(data3, time_col='date', value_cols=tz)\n",
    "    scaler_stock = Scaler()\n",
    "    stock_scaled = scaler_stock.fit_transform(series_stock)\n",
    "\n",
    "    return stock_scaled"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1b5b63f9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "729\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1cd26964fa0>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "stock1=darts_series(\"002758.SZ\",\"close\")\n",
    "stock1.plot(label='close')\n",
    "plt.legend(loc='best')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "57e552bc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "729\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1cd186f3d60>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "stock2=darts_series(\"002758.SZ\",\"volume\")\n",
    "stock2.plot(label='close')\n",
    "plt.legend(loc='best')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "96cb669a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GPU available: True (cuda), used: True\n",
      "TPU available: False, using: 0 TPU cores\n",
      "IPU available: False, using: 0 IPUs\n",
      "HPU available: False, using: 0 HPUs\n",
      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n",
      "\n",
      "  | Name          | Type             | Params\n",
      "---------------------------------------------------\n",
      "0 | criterion     | MSELoss          | 0     \n",
      "1 | train_metrics | MetricCollection | 0     \n",
      "2 | val_metrics   | MetricCollection | 0     \n",
      "3 | stacks        | ModuleList       | 6.2 M \n",
      "---------------------------------------------------\n",
      "6.2 M     Trainable params\n",
      "1.4 K     Non-trainable params\n",
      "6.2 M     Total params\n",
      "24.787    Total estimated model params size (MB)\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f3b359f364e044b2b6432eaf5bc78570",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Training: |          | 0/? [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "`Trainer.fit` stopped: `max_epochs=40` reached.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "NBEATSModel(output_chunk_shift=0, generic_architecture=True, num_stacks=30, num_blocks=1, num_layers=4, layer_widths=256, expansion_coefficient_dim=5, trend_polynomial_degree=2, dropout=0.0, activation=ReLU, input_chunk_length=24, output_chunk_length=12, n_epochs=40, random_state=0)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_stock1, val_stock1 = stock1[:650], stock1[650:]\n",
    "train_stock2, val_stock2 = stock2[:650], stock2[650:]\n",
    "model = NBEATSModel(input_chunk_length=24, output_chunk_length=12, n_epochs=40, random_state=0)\n",
    "model.fit([train_stock1,train_stock2], verbose=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "ad4e1ea0",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GPU available: True (cuda), used: True\n",
      "TPU available: False, using: 0 TPU cores\n",
      "IPU available: False, using: 0 IPUs\n",
      "HPU available: False, using: 0 HPUs\n",
      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "68cd954510a240e696231080f4a67963",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Predicting: |          | 0/? [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "model NBEATSModel(input_chunk_length=24, output_chunk_length=12, n_epochs=40, random_state=0) obtains MAPE: 40.70%\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1cd19673fa0>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pred = model.predict(n=len(val_stock), series=train_stock1)\n",
    "print(\"model {} obtains MAPE: {:.2f}%\".format(model, mape(pred,val_stock1)))\n",
    "stock1.plot(label='actual')\n",
    "pred.plot(label='forecast')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "1be6d188",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image(filename=\"covariates-highlevel.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b36f512a",
   "metadata": {},
   "source": [
    "## 股价时间序列预测中的协变量使用\n",
    "\n",
    "**时间序列预测中的协变量** 是可以影响预测结果的变量。这些变量可以提前知道或预估。在单变量和多变量预测模型中，协变量引入了目标变量历史数据之外的额外见解。例如，假日、特殊事件和经济指标等因素。此外，在多变量预测中，协变量扩展到包括相关的时间序列数据——这些可能是已知未来值或需要预测的变量（参见上述例子）。\n",
    "\n",
    "\n",
    "除了目标序列（我们感兴趣的预测序列）外，Darts中的许多模型也接受输入协变量序列。协变量是我们不想预测但可以为模型提供有益额外信息的序列。目标序列和协变量序列都可以是多变量或单变量的。\n",
    "\n",
    "在Darts中有两种协变量时间序列：\n",
    "\n",
    "past_covariates是指不一定在预测时间之前已知的序列。例如，这些可以代表必须被测量且不能提前知晓的事物。模型在进行预测时不会使用past_covariates的未来值。\n",
    "\n",
    "future_covariates是指直到预测周期都已提前知道的序列。这可以代表日历信息、节假日、天气预报等。接受future_covariates的模型在进行预测时会查看直到预测周期的未来值。\n",
    "\n",
    "**协变量**\n",
    "\n",
    "每个协变量都可能具有多变量性。如果你有多个协变量序列（比如月份和年份的值），你应该使用stack()或concatenate()函数将它们堆叠或连接起来以获得一个多变量序列。\n",
    "\n",
    "你提供的协变量序列可以比实际需要的更长。Darts会尝试根据不同序列的时间索引来智能地对它们进行正确的切片以用于目标序列的预测。然而，如果你的协变量时间跨度不够，你会收到错误信息。\n",
    "\n",
    "现在，让我们为“空气”和“牛奶”序列构建一些外部协变量，包含月度和年度的值。在下面的代码单元格中，我们使用darts.utils.timeseries_generation.datetime_attribute_timeseries()函数生成包含月份和年份值的序列，并通过concatenate()函数沿\"component\"轴将这些序列连接起来，以便为每个目标序列获得一个具有两个月份和年份两个分量的协变量序列。为了简化处理，我们直接将月份和年份的值缩放到了大约0到1之间：\n",
    "\n",
    "### 构建协变量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "fff0b2ac",
   "metadata": {},
   "outputs": [],
   "source": [
    "from darts import concatenate\n",
    "from darts.utils.timeseries_generation import datetime_attribute_timeseries as dt_attr\n",
    "\n",
    "air_covs = concatenate(\n",
    "    [\n",
    "        dt_attr(train_stock1.time_index, \"month\", dtype=np.float32) / 12,\n",
    "        (dt_attr(train_stock1.time_index, \"year\", dtype=np.float32) - 2020) / 12,\n",
    "        train_stock2\n",
    "    ],\n",
    "    axis=\"component\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "ddee500e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#air_covs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "d9179883",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='date'>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "air_covs.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3fecfdf9",
   "metadata": {},
   "source": [
    "### 协变量的使用"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "644d44cf",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GPU available: True (cuda), used: True\n",
      "TPU available: False, using: 0 TPU cores\n",
      "IPU available: False, using: 0 IPUs\n",
      "HPU available: False, using: 0 HPUs\n",
      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n",
      "\n",
      "  | Name          | Type             | Params\n",
      "---------------------------------------------------\n",
      "0 | criterion     | MSELoss          | 0     \n",
      "1 | train_metrics | MetricCollection | 0     \n",
      "2 | val_metrics   | MetricCollection | 0     \n",
      "3 | stacks        | ModuleList       | 6.6 M \n",
      "---------------------------------------------------\n",
      "6.6 M     Trainable params\n",
      "1.7 K     Non-trainable params\n",
      "6.6 M     Total params\n",
      "26.314    Total estimated model params size (MB)\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7db1572c1c994f3999446d56b03f4734",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Training: |          | 0/? [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "`Trainer.fit` stopped: `max_epochs=50` reached.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "NBEATSModel(output_chunk_shift=0, generic_architecture=True, num_stacks=30, num_blocks=1, num_layers=4, layer_widths=256, expansion_coefficient_dim=5, trend_polynomial_degree=2, dropout=0.0, activation=ReLU, input_chunk_length=24, output_chunk_length=12, random_state=42)"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = NBEATSModel(input_chunk_length=24, output_chunk_length=12, random_state=42)\n",
    "\n",
    "model.fit(\n",
    "    train_stock1,\n",
    "    past_covariates=train_stock2,\n",
    "    epochs=50,\n",
    "    verbose=True,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "4ee1b9f6",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GPU available: True (cuda), used: True\n",
      "TPU available: False, using: 0 TPU cores\n",
      "IPU available: False, using: 0 IPUs\n",
      "HPU available: False, using: 0 HPUs\n",
      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f1271793ca6b4a5593b01207335e04a4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Predicting: |          | 0/? [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "model NBEATSModel(input_chunk_length=24, output_chunk_length=12, random_state=42) obtains MAPE: 5.50%\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1cd0f222bb0>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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DLL7uwoULzYJM79690adPH6VNc0lpaWnOboLD8Rw9gzPOMSsrS7it0WhgMBgAANnZ2UhJSbHbcfjz8ww8R/cRHx+vaD/F4UOv1yM4OFjYDggIQG5urmz46NOnDyZNmoQNGzZAp9OhZcuWFl936NCh6N+/v7RRbl75SEtLQ2xsrOIE6G54jp7Bmefo4+Mj3Pbz80NBQQEAIDQ0FHFxcRV+ff78PAPP0XMpDh/BwcG4c+eOsF1QUACNRmO2n16vx2effYYff/wRQUFB+O677zB//ny88sorsq/r5+fntkHDGq1W6/FvJJ6jZ3DGORorHYA0fNy6dQubNm1Chw4dUKlSpQofhz8/z8Bz9DyKzzQhIQHHjh0DUBo8MjIyEB4ebrbf9evXUVRUhKCgIABAw4YNceLECfu0log8gnhgqfiPj1mzZqFbt24YOnSoM5pFRCpRHD7atWuHjRs3Yvfu3fjss8+QmJgInc68cBIWFobMzEzs3r0bZ8+exQ8//KC4D4iIvIOl8GG0YsUKNZtDRCpTHD5CQ0Mxc+ZMLFiwAOnp6Rg/fjw2b96MWbNmSfbz9fXFxIkT8cEHH2Dw4MEoLi7GCy+8YPeGE5H7shU+AGDz5s34/fff1WoSEalI8ZgPAEhMTMSiRYuE7c6dO6Nz585m+3Xq1AmdOnWqcOOIyDMVFxcLty2Fjy5dugAAjh49invvvVeVdhGROrxndAsRuQxx5cPf39/qvjNmzHB0c4hIZQwfRKQ6Jd0uRnJjy4jIvTF8EJHqyhI+fH19Hd0cIlIZwwcRqY7hg1xBdnY23njjDfzyyy/OborXYT2TiFTH8EGuYMKECfjPf/4DoPSaZPZYXZeUYeWDiFTHMR/kCozBAwB27dolu09aWppkdW+yD4YPIlKdkqm2Rqx8kBpu3bpldt+mTZsQFxeHevXq4e7du05oledi+CAi1ZVlqi3DB6lBLnx07doVBoMBmZmZWLx4sRNa5bkYPohIdRzzQa5GLnyIsevFvhg+iEh1HPNBrkB8ZfacnByr+4qvxEwVx/BBRKpj5YNcQWhoqHB77ty5SE9Pt7ivXq9Xo0leg+GDiFRXlvCh1fLXFDmGOHwAwGOPPWaxwsHwYV/8VBOR6soSPsT7EtmTj4+PZPvEiRMoKCiQ3ZfdLvbF8EFEqivLVFuGD3IUuaBRVFQkuy8rH/bF8EFEqivLVFuGD3KU/Px8s/sKCwtl92X4sC+GDyJSHbtdyBXIhQ9LlQ92u9gXwwcRqU4cKGzNZmH4IEcwGAyy3S6sfKiD4YOIVMfKBzlbcXGxbKDgmA91MHwQkeoYPsjZ5LpcgH8qH6Zhw1IoofJh+CAi1ZUlfIhnxhDZi6XwYQwZY8aMkdxvqTuGyofhg4hUJw4UHPNBzmCr8vHZZ59J7re0/geVD8MHEalOHCh0Op3VVUwZPsgRbFU+TDF82BfDBxGpThwofHx8zFaa7N69u+y+RPZiq/JhiuHDvhg+iEh1tsKHeOGxsoSP/fv3o2fPnli5cmXFG0kejZUP5+K1qolIdbbCh3gQalnCx/333w8AWLlyJc6fP1/BVpIn89TKR3FxMXbu3Im7d++iffv2CAkJcXaTZDF8EJHqHBU+xLgiJVljaRaVpcqHMZQYDAYUFhbavCyAswwYMADLly8HANSpUwenTp2CTud6X/XsdiEi1Tmq20WM6zKQNeLwERgYKNy2VvkoLi7G/fffj6ioKPz5558Ob2N5/Pbbb8Lt8+fPIyUlxYmtsYzhg4hUJ/7Fr9PpHFL54PogZI34fSUOH9bGfKxYsQIHDhxATk4OunTp4vA2lodp91BeXp6TWmIdwwcRqc50qq0jwgcrH2RNeSof165dE7ZzcnIc17gKMA0fd+7ccVJLrGP4ICLV2ap8sNuFHK08lQ+NRiO5LyWjGAnPXkGHl6+gpMT5Y4yM41HEGD6IiP6fOHw4asApu13ImvJUPiSL4fmEofazWpzKqIodyVUxc0G6w9qqVHFxsdlAa3a7EBH9PzXGfLDyQdaUtfJRWFgorXzUnyd5fMmaM/ZtYDnITQdm5YOI6P/ZGvPBbhdytApXPqo+K3n8Tr7zu13kwoerVj5cb/IvEXk8druQs1mqfCxduhQBAQFm+5uFDxN3XWANMrngxMoHEdH/Y7cLOZulysfhw4cxevRos/3lBpxKHi+0/Jha3KnywfBBRKpTo9uFlQ+yxlLlwxKb4aPYx+JjauGYDyIiKxzR7WK6HysfZI2lyoclRUVFVgOtHs5fbp3hg4jIClvdLr6+vsJtpeHDNGyw8kHWlLXyAdj4IteajxNRm7Vul6KiImzatAlXrlxRu1myGD6ISHW2ul3E1RCl4cM0bLDyQdaUtfIBWA8fBk1gubsI7cXagNMpU6aga9euuP/++53eToCzXYjICWxVPozho6SkpNyVD4YPMlVYWIiBAwfizz//lFxwTWn4yM3NtfygNhB3795FcHBwRZtZbnKVjytXruCDDz7ABx98AABITU3FlStXUKNGDbWbJ8HwQUSqMx3zIR7jAUgDSXkrH+x2IVO//PILVqxYYXZ/pUqVFD3favjwCUJeXp7LhY/Nmzdj8+bNkvvu3r2rVpMsYrcLEanOtNvFNHyUp9uFlQ+y5e+//5a9v1q1aoqebzV86MJw4IT8AmVqkQsfchg+iMgrmXa7iAeYAgwf5BgnTpyQvb9q1aqKqh9WwweADX/6Wn3c0cThIygoyOJ+rrD2B8MHEamuLN0uSrtP2O1Ctpw8eVL2fp1Oh9jYWJvPtzVt9cZtfbnaZS/iAafdu3e3uB8rH0TkldjtQs5w8eJF2ft1Oh1q1apl8/n/VD7kFxvLu+vcwCuufFgLU6x8EJFXMq18mHa7+Pr6QqcrHQ/P8EH2oNfrLf7F7+Pjo6jyIYQPjXz3yt0C51Y+xOHDWphi+CAir2QMHxqNBlqt1qzy4e/vz9kuZFfWuhp0Oh1iYmJsvoY7hQ9rg2jZ7UJEXskYKIzVDdPwERAQwG4XsitrX7g+Pj6IjIy0+RpC+ND6yT6eX2AoV9vsRRw+xNdHAiAJV6x8EJFXMlYljOHDtNulPJUPLq9O1lj7wtXpdIiIiLD5GrYqH/mFzg0f4gGn/v7+ePTRR4XtMWPGCLcZPojIKxmDgTFgOKLbhZUPErNV+VASPoTZLhbCR4GT33L5+fnCbX9/f8yePRsDBw7E+vXrUbduXeExdrsQkVcyrXzYI3yw24WsKW/lw7T7AoDFbpdTWfE4leq86seNGzeE2+Hh4WjWrBkWL16MJ554QrKOCSsfROSVTMd82KPbhQNOyRrxX/vG952RtcqH7OJjFiofAPDEeNcIH6bnw/BBRF5PSbeL8QtCaYhg5YOsEYcP0y9ma5UP+fAhX/kAgPPp5WufPVgLH+KL57HbhYi8kq1uFz8/vwqHD1Y+SEz8177pzBZrlQ/ZC8VZqXw4kzF8aDQahIaGSh5j5YOIvJ6tbheNRiPcV1JSAoPBdinbNGyIR/4T2ap8iCsDYl26dDG//LyFMR/OZgwf4eHh0GqlX++sfBCR17PV7QJIA4mSLhTTfWxdBIy8i/ivfdPw4ePjA41Gfsn0iIgIpKSkSO908cqHXBVHfKE5V/hsMHwQkepsdbsA0vChpAvFNHzcunWrIk0kD2Or8gEAixYtMnueTqeDTqfDPffcU3pHaDsgZpTD2lleer0eN2/eBCAfPiIiIoSAlZ2drWbTZJUpfCxbtgxdunTBsGHDJANbLPnggw+wdOnScjeOiDyTrW4X8WOAssqHaUC5fft2RZpIHsZW5QMABg8ejMaNG8s+JixXXuMVoEovB7a0fM6dOwe9vnR5d7nw4ePjgypVqgAAsrKyVG2bHMXh4+TJk1iyZAmWL1+Ovn37Yu7cuVb3P3v2LPbu3Ytnnnmmwo0kIs9S1spHebpdGD5ITFz5MB1wKg66pu9F42NC+Ci45KAW/uPYsWM4ceKE4v3PnDmDBg0aCNuWBs8az8EVwofO9i6ldu7ciaSkJISHh6Njx4745ptvrO4/e/ZsDB8+XPYvGrHCwkKzgWFyl9h2F8bkafy/J+I5egZnnqN4zIderzdbd8H0voKCApvtFF/XAijtduHPz73Z8xyF1UlROiBTTKPRCMcw/c7SarXS96OC8FGW9pqe4x9//IEHH3wQPj4+2Lt3LxITE22+xn//+1/JdkJCgmwbqlWrhuTkZOTl5eH27duScSD2YjrQ1RLF4ePq1ato27YtgNIflE6nw927d2VHCO/evRsHDx5EYGAgTpw4gREjRshPVwKwcOFCsyDTu3dv9OnTR2nTXFJaWpqzm+BwPEfP4IxzNHa7lJSUICUlReirNkpJSZFUMi5evGhz9kpmZqZk+/bt2/z5eQh7nOOVK1eE26YL16WnpyMnJ0f2sVu3biElJeWf8FJ4WfJ4rapFSL0qDSxnz55FWloa4uPjLQ5kNWU8xzfffFNox9ixY7Fw4UKbzzUdQJqYmGg+SBbSQaeHDh1CbGysoraVRXx8vKL9FIcPvV4vCRABAQHIzc2VDR/fffcdWrZsiaeffhqrVq3C9OnT8dFHH8m+7tChQ9G/f39po9y88pGWlobY2FjFCdDd8Bw9g7POUa/XC3+VBQUFIS4uDtHR0ZJ94uLiJOsUREVFIS4uzurrmi4GVVBQgGrVqlmcQunu+B4tG/F3Sp06dSSPxcfHC++TkJAQyWNVq1ZFXFwc/vWvf2HdunXw1V+BuINv2gu+eP596bEmTpyIlStX4qWXXsKXX35ptV3Gc6xRowYGDRqEnTt3Co+dOHHC5vseMO9m6d69u+y/V+3atYXbvr6+il7bURSHj+DgYEnZqqCgwGKiO3bsGJYvX45atWqhUaNGePLJJy2+rp+fn9sGDWu0Wq3H/kIw4jl6BrXPUfyXpY+PD7RardnvEq1WK/m9UFJSYrONcpURR5WWXQnfo8qI33dhYWGSx/z8/ITXN+128fX1hVarRceOHXHo0CHcyg/Bw+P/ebx9Mw0A6To0K1euBAB89dVXmDdvnqL27du3DytWrJDcl5WVBYPBIAx6tUQ8nmX58uVm3ZhGwrgVlM54ceb7RvGRExIScOzYMQClwSMjI8Os38woPDwcUVFRAEp/qJ7+4Sci5cRfAsZfknKLiJV1wKn4ip5Gpt055L3Es6FMhwGIv9xNw4f4sebNm6NtS2nVpI7J+mPlZez2MSX+o98S8UyemjVrWtxPXCGxdDy1KA4f7dq1w8aNG7F792589tlnSExMtJiumjVrhl9//RUA8Msvv6B58+Z2aSwRuT/xl4Dxd4jc4Liyhg/TAaeA83/BkusQh17TP4jFFQDT8GH6PafTaTCmDxDoD8x7XaN4TIctlt7jShYEE4cP2WvR/D9xl5Kz18FRHD5CQ0Mxc+ZMLFiwAOnp6Rg/fjw2b96MWbNmme37+uuv49dff0WnTp2wZcsW/Pvf/7Zro4nIfYnDh/GvSluVDyWLjMmFD1Y+yEj8HrJWjQ8ICJBsy83Y/PhVLW5v0uClHqXBo2mQ9dmfSqgRPsTjqJw9FV3xmA+gdASteAW4zp07o3Pnzmb7Va1a1eYgGyLyTkq7Xcq6yBgrH2SNOHxYWwKiT58++OWXX1BUVIRq1aqhU6dOsvv5+PxT8WhWdQ+O3hleuqE3f6+mpaVh1KhRaNq0KaZPny77emqHD7epfBAR2YNct4txGj8AvPTSSwCUdbssXrwYw4cPR1paGsMHWSX3vpPTs2dPZGRk4MSJE0hNTZUM0rTk+eeHwifvQOmGVhpsDAYDhg8fjlWrVmHGjBnYvXu37GuI3+NlvQ5Lebpd3KryQURUUXLdLtWrV8eWLVtw6NAhvPjiiwBsh48LFy5g8ODBAErXcJAbuW8aPvbv34833ngDvXr1wssvv1zxkyG3oTR8AEDlypVRuXJlxa/doUMH3N+qBH8kG+/RAigdx1RYWCiMgQSAgwcP4sEHHzR7DfF7PCIiQhhoysoHEZEdyHW7AEDHjh0xduxY4RekrTEff/75p3B77dq1iiofbdq0wdatWzFy5EiXuLInqacs4aM8fHWigaeaf17fdAq46SJmRqbhw6gs4UOj0cDf39/ifq5U+WD4ICJVKf0SsDXm49q1a5JtJQNOxb/4xVMYi4uLJStgkucxfd/169cPANCtWze7vL5OvBSH5p8NpeFD3L7yho/AwECrs29Y+SAiryXX7SLHVreLkvBhbcyHsR0lJSVo0aIFatSogV9++cVyw8mtmYaPb7/9Flu2bMGPP/5ol9eXhg/pdYnEjBeBa926taS7xB6VD2tdLoB0LAkrH0TkVZRWPuwRPqxNtX3mmWewfft2/Pbbbzh69Cj0ej169XK9S6WTfZi+7wICAtCxY0e7Lb/vI/42rTlOCCCmlY9vvvkGZ86cwb59+7B+/XrhfjXCh1arFbpenF354IBTIlKVpTEfpmyN+cjOzhZuh4eHC+FDo9EIU3dTU1OxZcsW3HfffWYDCPfu3YuXX34ZM2bMKN+JkFtRWnErL0nlo9YkIKV0Sq146XNT4gCgNHz8/fffuHDhguQ+YxXDVvgASsd93L59m+GDiLyLvbpdrl69KtyuXLmysLx6eHg4cnNzUVRUhCNHjqBTp04IDAzEuXPnzF7j5MmTNq+W62hLlizB77//jkmTJqFGDTut1U1mjO87R10LR2f2Vi4N2SNHjrT8HAvjmiyFj+XLl6Nv374WX09J+AgNDUV6errTu10YPohIVfYacCruL/f39xd+mfr7+6NevXrYv3+/8Pjdu3exa9cu2eM4M3xcvnxZuKr36dOn8b///c9pbfF0xvedI2a6lL6u/P3bt2+3+Bzx9YjE7/HIyEjhtjgk2Hp/KLmUSc2aNXH37l2EhYXBYDDYbXn4smL4ICJVlafbRS58iENMcXGx0O0SEBCA5cuX48svv0RycjI2bdoEwHL525nh49SpU8LtLVu2OK0d3sDR4cOnHMUU8Tgl8Xu8SpUqwm3xoGlxV8mECRMkV+etXLkynn32WZvHdJWAy/BBRKoqT7eL3JgP8X0FBQXCL3J/f3/ExcXhlVdewbZt22yGD2t98o7m5+fntGN7G4dXPsoxjMRS5UMcPsSDpsVVkAkTJki6Z9wNZ7sQkarsNdtF/DqFhYWS8GEkvkiYpZkvavZ9JycnY+HChUI/viPGHpA8dwof4eHhQjstVT7EC4a5I1Y+iEhVjuh2ycjIEG6Lw4d4GuWNGzdkj6NW+MjPz0e7du2Qk5OD5ORkzJo1S3Z6MDmGK4YPS90uvr6+CAsLw7Vr1ySh2Rg+AgMDHXYeamHsJiJV2WvAqVxXDGC58uHs8HH8+HHhr9iPP/4YgPQvX3IsNcd8aP7/ui5yRowYIdy2VPnw9fVFeHg4AGnlw/heFa9U6q4YPohIVfaaamspfDzwwAPCbVcKH3IYPtTj6PAhnjSi1Ros7jd8+HDhtrXwYRxMevPmTWHdGmPlw927XAB2uxCRyuy1yJjcfY899hjeffddYVtJt4taiy2JryVjZBo+iouL3b6c7qqM7xdHLDAGACWiYodOq4f8FVykgdhat4ux8lFSUoI7d+7g6tWrwnuYlQ8iojIqz4DT9957DwkJCfjss89kX8eoX79+kucpqXyI+9QdueaBXMgxHfPh7IWfPJmjKx/ForRhqfIxceJESbegksoHUNr10rNnT2HbEyofDB9EpCql3S6mXxKnTp3C+PHjhcXF5K4OavpLWUnlQ3y/I6e+moYPg8FgVvlw9pLXnsz4flEjfPjIhI+GDRvizTfflARiJWM+AGDHjh04fPiwsG16XSN3xPBBRKpS2u0i/gvRqLCwUOi+kKt8mJajlVQ+nBU+8vLyzMLHkSNHHHZ8b+foykeR6O0oFz6++uorhISEKO52EV+LyLgKrtHp06ft0WSnYvggIlUp7XaxtICS8Ze0XPiwVvmwtM6HWuHDtEvl5s2bZuGjR48eVpfjpvJTs9vF10caPqpXr4527doBgMVuF/H72dfXF88884zFbsDY2Fh7NNmpGD6ISFVKu13E17cQK0v4EP+VaYn4GjFqVj5u3Lghu86HcUVWsi81w0dgoD+qVasmbI8ZM0Z4r8t1u5SUlOC3334T7vf19UXr1q3x6aefIi4uDjExMUhKSoKvry90Oh2++OILh5yDmjismohUpbTbxdKgOuO1WOwVPsQcOdPENHzce++9svtZ6h6i8tPr9dDrS6ejOOpnLB6C5OerxemUFCQnJyMyMhLx8fHCYzqdDlqtFnq9Xgifa9askbyWcdD0qFGjMGrUKOH+wsJC3Lx5UxJs3BXDBxGpSmm3i6WSc1kqHzqdDjqdzuKaIKaMX1COoHQmC8OH/SkNvBVRJAofOp/S4NuiRQuz/TQaDfz9/XH37l2h8vH666+b7SPHz8/PI4IHwG4XIlKZ0m4XS4qKimAwGBSFD0A67sMWuRk09qJ0JgvDh/0pDbwVOoZkzIf1fY0VOW9eXp/hg4hUVdEvgqKiIosVCvEaH0amXS9JSUmK2mZv4vAxceJEi/sxfNif2uHD1iGM78n8/Hxh9VJvw/BBRKqqaAm8qKioTCFBXPnw8/PDmjVrsHDhQtl91Qof4jEAphg+7E/18GGj8mGc8ZKfn4+srCyHtMfVMXwQkaoq2u1SWFgo2z3SrVs32f3FlQ9jt0xQUJDNttmbccxHUFAQoqKizB6vVKkSAIYPR1AjfJSUIXwYVy+9fv060tLSHNIeV8fwQUSqKssXwbhx48zuM618tGrVCitWrMAPP/wg+xrilSKNVRBLU2rVqHyEhoaiatWqZo9Xr14dQOn6H44c+OqN1Agfc0b/M0j0i39ZX6a/du3aQrtMF5aTW1zPE3G2CxGpqizdLlOmTEFkZCR++uknHDx4EIB5+KhatSp69+5t8TXEVQbj7AJLv+DVCh9VqlQxezw6Ohrnz5+HwWDArVu3JKGJKkaN8NEyQYM9c0uvbtviHuvhQ9zttn//fslj3rLIHMMHEamqLN0uISEhmDhxIvR6vcXwYevLRFxlMC7NbumLvbi4GAaDwe4XmDMYDEK3i1z40Gg0qFGjhrB97do1hg87UiN8AECbJsreN5bCx3//+1888MADdm+XK2K3CxGpqjxfBOJZLGUNH8HBwcLtu3fvAgDuv/9+PPPMMwgODjZbqtoRXR55eXnC64aEhCA8PBxa7T+/fkNCQhAdHS1sX7lyxe5t8GZqhQ+lxOFDfME4ue44T8XwQUSqKs9sF/EYDdPwYat6Ije4VKvV4scff8Tt27eRmpqK9u3by7bPXsQzXUJDQ6HVaiWVjbCwMEn4yMzMtHsbvJmrhY8mTZrI3s/wQUTkIOWZ7SKufBQWFpbpy8TSzBYx8Ws4YtyHafgApBfOCwsLEwacAgwf9uZq4SM+Pl4YdCrG8EFE5CBqd7vUrVtXuG1pfQ1Hhw/x0urG8CHuDgoNDWX4cCBXCx8A0KVLF8m2pVlQnso1fgpE5DXK0+1SkfDRu3dvzJs3DydOnMDy5ctl91Gz8mFca0Rc9dFoNAwfDuSK4WPq1KnIz8/H5cuXUVJSgtdee82hV1V2Na7xUyAir2GPykdZAoyPjw927NiBkpISi908zuh2EQ841ev1kvCRkZEh3DYYDNi6dStCQkLQunVru7fNG7hi+IiOjsaiRYug1+uRkpKCuLg4ZzdJVa7xUyAir1GeMR/WBpwq/TKxdizxY44IH8ZZNsA/C52Jp/Pq9XrJ9Nvr168Lt//3v/8JJfrjx4+jYcOGdm+fp3PF8OHtOOaDiFSldreLEo6ufIhf03guppUPnU4njAO5efOm8Njzzz8v3J46dard2+YNKno9IbI/hg8iUlVFu13KOttFCfFrOGKqrVx7TcMH8M/iZ+LwIW5bYWGh3dvmDVj5cD0MH0SkqopOtfWUykfz5s2F+4y35cKHuMuJ4aN8GD5cD38KRKQqb+92MR7r7bffxvbt21FSUoL33nsPwD/hIy8vD4WFhfDz85Nch6agoMDubfMGDB+uhz8FIlJVeb4IKrLCqRLOCB+RkZFITk4G8M/gU/Gqpzk5OahatSorH3Zg7/cLVRy7XYhIVd7Y7VJUVCR7LI1GI5n1Ig4fn3/+OQB2u9gDKx+uh+GDiFRV0W4XRww4dfRUW6XtFYePmTNnQq/XS8JHQUEB5s2bh48//tgh7fRUDB+uhz8FIlLNrVu3sGHDBmFbjUXGlHBGt4sc08pGdna2JHwcOXIEI0eOBFC6SFWbNm3s3FLPxPDhelj5ICLVPP7445Jtb+l2Udpe8WJkAHD58mWL+3/66ad2aZs3YPhwPQwfRKSavXv3CrcbNWqESpUqKXqePVY4tcY03Nib3FRbOa+88opkOz093eIMl+joaPs0zgswfLgehg8iUoVer4fBYBC2t2/fLhlsaY34Czs1NRUDBgwQtu3xZWIabuxN6Zdf69atJQHk8uXLyM/Pl923Ro0a9mugh2P4cD0MH0SkCvEXQPv27ct0+fCAgADh9u+//y4Z82G8VkpFOHpGiaXZLnLEXVMjRozAH3/8IbufeP0Pso7hw/UwfBCRKsryBWzKeM0TUzExMUhKSqpQuwDHh4+yfPkpvbppXl5ehdrkTRg+XA/DBxGpoiJfAP7+/mbPiYyMRFpaWpkqKJa4Uvho0qQJBg8ebHZ/lSpVsHjxYmHbdHAqWcbw4XoYPohIFUoHXcrRaDRm1Y/7779f8ZgRW1wpfGg0GixatMgsgAQEBODhhx8Wthk+lGP4cD0MH0Skiop+AZiGj0aNGlW4TUauFD6MmjRpItn29/eXjG9h+FCO4cP1MHwQkSoqMuYDMA8fPXv2rHCbjNQMH0qrPg0aNJBsBwQESMKHpVkwZI7hw/UwfBCRKir6BRASEiLcrlGjBtq2bWuXdgEwW8Lc3soTvKpUqSLZNg0frHwox/Dhehg+iEgVFRnzAUin1EZERNhtvAfgmt0ulStXlmz7+/vDx8dHaCvDh3IMH66H4YOIVFHRLwBxRULpyqhKuWL4iIyMlGwb1zoxhjBx+ODVbq1j+HA9ZQofy5YtQ5cuXTBs2DDcuHHD5v45OTl47LHHyt04IvIcFR3zIV7XIigoyC5tMnLF8BERESHZNi4qZgwfeXl5OHfuHBITE1GpUiXMnz/fTq31PPa+ECFVnOLwcfLkSSxZsgTLly9H3759MXfuXJvP+fzzz3Hz5s2KtI+IPERF//q8c+eOcNsbKh+m+9WsWRPAP+EjLS0NnTp1wpEjR1BSUoLvvvvOTq31PKx8uB7F4WPnzp1ISkpCeHg4OnbsiKNHj1rd/++//8a5c+cQFRVV4UYSkfur6JgPceXD3uFDvFS5q4QPU8bZL5bGuty6datcr+sNGD5cj+KfwtWrV4XR5RqNBjqdDnfv3pW9rkJJSQk++ugjTJ48Ga+//rrV1y0sLDT7sOt0OslfIu5Er9dL/u+JeI6eQe1zFI/Z8PHxKfNxxYElLCzM6vPLem7iL6SCggK7/5uIu5zKc+4AUKdOHej1epw/f1728dzcXFV+lllZWahatapdB/xaYq/3qPjfX6vVutTn2tN+12i1ymoaisOHXq+XzLMPCAhAbm6ubPhYsWIFWrRoYTZPXc7ChQvxzTffSO7r3bs3+vTpo7RpLiktLc3ZTXA4nqNnUOscL1++LNzOy8tDSkpKmZ7/9ttvY/DgwdDpdBg8eLCi5ys9t+zsbOH29evXy9w2W3Jzc4Xbly9fLtcfVzqdzqxdX3zxBT788EOkpqbi1q1bdm+3qSVLlmDy5Mlo164dvv/+e4ceS6yi71Fx939WVpbFawU5k6f8romPj1e0n+LwERwcLOlzLSgokE2+2dnZWLNmDRYuXKjodYcOHYr+/ftLG+XmlY+0tDTExsYqToDuhufoGdQ+x3Pnzgm3IyMjFV9AzahWrVqoX78+wsLCkJCQYHXfsp6buPrq5+dX5ralpqZi165dePLJJyXrkRiJKyt169ZV/O89a9YsjB07Fo0aNcLjjz8uBC/j+I727dvj66+/BlAa6Mra7rKaPHkygNIrC/v4+AjjUBzFXu9R8VWRa9Wq5fB/p7Lwht81chSHj4SEBBw7dgwdOnRAQUEBMjIyEB4ebrbf/v37kZmZiR49egAAbty4gS5dumDZsmVmo7eB0g+6uwYNa7Rarce/kXiOnkGtcxSXlf38/Mp1zDZt2pRpf6XnJv5yKioqKlPbDAYDHn30UVy4cAEvvviiEAbEjGMOjF3WSo0ZMwadO3dG3bp1hd+TH3zwAerWrYtHH30UwcHBQtjJz8+HXq9XbUxDQUGBap+Nir5HxbNdyvveczRv+F0jpvhd2q5dO3zxxRdo3rw59uzZg8TERNk3edeuXdG1a1dhOykpCWvXrrVPa4nIbVV0qq0jVWS2S25uLi5cuAAAmD9/vtXwUdbz1mg0uPfeeyX3RUVFYcqUKdDr9UhJSZFMO75z5w7CwsJgMBgwf/58BAQEYNCgQQ4Zn+GIlWAdhQNOXY/imBUaGoqZM2diwYIFSE9Px/jx47F582bMmjXLke0jIg/hyl8AFQkfSq6xUt7woYR4/IJxbMmiRYvw0ksvYciQIdizZw8MBoPk398exN3wcm7cuIHXX3/dbEyfM7jye89blemnkJiYiEWLFgnbnTt3RufOna0+h1UPIgIqPtXWkSpybRfxFGBLjFUftcLHyJEjhfveeecdnDlzBrdv38bu3btRr149uxxXPIhWzrx58zB79mwAQExMDJ544gm7HLc8xO89Hx8fp7WD/uE9HUxE5FSu/NdnRSofSsKH8dwdEbrE4WP79u0ApNWYjRs34uzZs7hy5Ypsl1B52Qof4tkwY8aMsdtxy8OV33veiuGDiFThymM+xKGgrOFDyQXe1Op2eemll5CZmWlx32PHjtntuLbCh3isyqlTp+x2XLHk5GQsWrQI//vf/ySDSk0xfLgehg8iUoUrfwFotVqhTfaofGzbtg21atUSuj8cGT7EM3UAIDo62uK+9rwSrq3wYfrvaO9LbRw/fhxNmjTB0KFD0blzZ3z66acW93Xl9563YvggIlW48pgP4J+ul4qGD+PU27S0NMybNw+pqakODR+WVjyVI15rpaKWLl2KTz75xOIYGdNwcuLECbsdGwD27t0r2d6xY4fFfRk+XA/DBxGpwtW/AIzh49ixYxg3bpzi55lWE0xnvxQUFDg0fLRo0ULxvpcvX1Y0O0eJHTt2YMyYMfjyyy9lH3d0+DANPeJVak1xwKnrYfggIlW48pgPAKhatapwe9asWbh69aqi55lWPky3CwsLhddyxHkPHToUXbp0QdeuXTF9+nSr+xoMhnIvwW5pqq7x+l1bt25Fr169sG3bNgDmU3EvXbpUruNaUp7w4ePjo8o1acg2hg8iUoWrVz4++ugjybatMQ1GpmHDtBLSpEkT4bYjzjs0NBSbNm3Chg0b8Mgjj9jcvyzdNGLWpiAbDAb06dMHv/zyCx599FEYDAazf7+cnJxyHVdpe5SED1d833krhg8iUoWrj/no0aMHBgwYIGwrXZTLNGxYCy1169YtX+MUuueee2zu44jwkZqaiuvXrwvbaWlpZv8O9h5wajo258aNG5Lqmpgj11mh8mH4ICJVuHq3CyANRZa+yEyZVj7S09Mt7jtnzpzyNUwhcdeRJY4IH1u3bpVs79mzx+HhQ6494gAkdvv2bQCQvegfOQfDBxGpwtW7XQBpu+QqH8a1JDZt2oT69evjrbfeMgsfli6NvnDhQtSuXdt+jZWhZDzD8ePHy/Xa1gaqbtiwQbJ95MgRs/3VCB+Wul4YPlwPwwcRqcIdwoe1ysfnn3+O0NBQTJ06Ff369cPZs2cxc+ZM4aJyRkOGDJF97erVq9u9vXL69u1r9fFNmzZhx44dMBgMZXpd8Zf94MGDJRWejRs3SvZNTU01e74a4SMrK8vsPoPBgFu3bgEoHR9DroHhg4hU4epjPgDrlY9Ro0YhLy8PM2bMwI0bN4T7N2/erOi1o6Ki7NNIG+bMmYMpU6aY3R8RESHc7tChA7RaLerXr6+4G0b8Ze/v74/o6GjhNU2rP3LTav/66y/MmjULK1assMtF7uTWYzl9+rTZPtevXxcqVqx8uA6GDyJShaeO+bC2nLmYWpWPqlWrYsaMGUhMTJTc//LLL5vte/bsWYwfP17R65qGDwCIi4uT3ffQoUOy948bNw7PPvssvvrqK0XHVNoeo7///lu4nZOTg7p166JKlSrCfax8uA6GDyJShTt0u9ga81ERSgaD2tPo0aOFv/S7du2KmTNnyl5lfOXKlYqWXReP4bAVPmxZs2ZNuZ4nJhc+xNeumTt3rtnaIqx8uA6GDyJShTuED3HloyLhw/T6Kr6+vqqf86BBg3Djxg0UFBRgw4YN0Gq16N69u9l+er3e6hoZRuIve+P1ZGxVc1544QXZ+/fu3Wv1QnBKyHW7nD17VrhtHOchxsqH62D4ICJVuNuYD3G3i60umJo1a0q2TdfzMF7qXm0+Pj7CsvFG9evXN9vv2rVrNl9LrtslMDDQ4v61atXCggULMHHiRAClgeyJJ54AUDr7xHR8RlmJ2xMeHg5AOvYkMjLS7DkMH66D4YOIVCEu25t+IboKS5UPW90S999/v2TbNHxUq1bNDq2zj4ULF5q1p7zhY+jQodBoNNBqtdizZ49k/zZt2gAApk2bhp9++gm7d+9G48aNhcflZqaUhVz4EP+cgoODzZ7DbhfXwfBBRKoQzxARz7xwJZYqH6azOUzVqFFDsm0aPqxVCNTWrl07ZGZmYtasWcJ9SrpdMjIyhNvGn1/Tpk1x/PhxHDt2DG3atEG9evWEfZ566ikApUGlV69eqFOnjqQaYWlBMKXkwkd+fr4whVhuTAgrH66D4YPIi6WmpmLWrFm4ePGiw48l/rJx1fBhqfJhK3xotdJfpabho1KlSnZonf1oNBpUrlxZ2FZS+RAP5hRXMBISEtCwYUMAwPvvvw9fX1+0bdsWvXr1MnsNe4YP8ZgPcagwVtjkwgcrH66D4YPIiz3//POYMGGC5JomjmKsfAQGBgoDFl1NeSsfiYmJeO211wAArVq1kkzvBFyr8mEkbqOSyod4Gqs4fIj16tUL165dw+7du2XH9Tii8uHn5ycJd8auF7kVWeXGu5BzuOaQcyJyOL1eLyww9fvvvzv8eMYvG7mBgK7CUuXD9PLwQOmYBr1ej5o1a2LAgAHo168fevbsiRYtWuCvv/6S7GscI+FKxOFj6tSpqFGjBl544QXJEu0pKSnYv38/2rZtK5xTbGys1e4La9UFR4UPcbiTCx8xMTGYNGkS2rZtW6Fjkv0wfBB5qStXrqh6PGPlw1W7XADllY8PP/wQgwcPlgzc9PHxQYcOHQCYD6hVcs0VtZkOOh0+fDj8/PwwaNAgAKXh6+GHH0ZKSopkP+OMlfJwRPjw9/e3GT5++uknPPDAAxU6HtkXu12IvJTp9Tcquu6CNfn5+cKXgitXPiwtMiYOHzNmzMC4ceOszmBxxUqHqfj4ePTp00dyX3JyMgDg8OHDGDBggFnwqFSpEt58881yH9MRYz6UhA9X7ebzZgwfRF4oKysLmzZtktxna1xDRbjDTBfA8vLq4n8bJYNHXXUqsZhGo8Hy5cuxc+dO4T7jeT755JNYvny5ZP9mzZph/fr1qFWrVrmP6azKB8OH62G3C5GXuXDhAhISEsxWiLxz547DZgOIw4e7Vz6UhA93qHwYiWe93LlzB3q9HmlpaZJ93n77bUyaNKnCxwoKCoKvry+KiopUDR/u9PPwFgwfRF7mt99+k12aOjc312HHFF9jQ/xl52rElY87d+5g8eLFOH/+PA4cOCDcHxQUZPN13KHyYSQOU3l5eZKgaGSvi+JpNBpERkbiypUrqg44ZeXD9TB8EHkZuSmIgPyMDnvZt2+fcLtZs2YOO05FiSsfX331FS5fvmy2j5Jps6brfrgycZjKy8vD1atXzfax5xV57RU+OObDvbnPJ4SI7EK8BLV4ZU5HVj7E4cN0KXJXIq58WAoeDz30kM3XcdUL58kRVz7u3LmjSvgASt9vchU4JfR6PfR6PYDSn5k4fBhDB8OHa2P4IPIy4l/K4vEXjqx8nDp1CkDpX9muvNCTpdCwePFibNq0CampqYq+iKOjo9GtWzf4+Phg4cKF9m6mXYm/uPPy8mSvuWK6fHxFiN9zcl08SogHA5uGD2O4lrsWDbkO94nnRGQX4vAhnnniyMrH7du3AZR+8bjimhdGlq6227179zLP0lm7di1ycnKE6464Kq1Wi8DAQNy9exd5eXk4c+aM5PGRI0ciOjrabscznfESFRVV5tcQhw+dTme128XPz8+tusG8BX8iRF5GHD7EX4yOrHwYg43clUZdiaXKR3kuSKbRaFw+eBgZu16OHj2KN954Q7h/9erV+PLLL+16LHtMtxXPRDKtfLz66qswGAzC+5xVD9fE8EHkZSx1uziq8mEwGNwmfFiqfPj4+KjcEnVZmsFzzz332P1Y9ggfpt0upmM6Tp8+LbzPOd7DNTF8EHkZ8YBT8V/mjgofd+/eFS5z7urhw50GitqT3Nol//nPf9wmfJheRfjKlSsMHy6O4YPIy1iqfFR06qMl4lDj6uHDUuXD05mGj0cffRRDhw51yLEcET4aNmyIVq1aCfdlZWUJIZvhwzUxfBB5GXH4aNSokXD78OHDDjmeO4UPb618mHa7VGQJdVvsHT6MP7ORI0cK94nDh5J1WUh93vlJI/Ji4vBRp04dVKtWDVlZWdi3bx8MBoPdZqOcP38eGzZsQIMGDYT7XD18sPJRyp3Ch/FnJr7QX2ZmpjDVVsly+KQ+Vj6IvIx4zEdAQABatmwJoPSLYNu2bUhMTETt2rWxYsWKCh3nmWeewWuvvYZ+/foJ9znq2jH2wspHKVcPH6azXQBp+BBfjZeVD9fE8EHkZcSVDz8/P9SpU0fYnjBhAg4dOoSUlBS8/vrr5T5GUVERDh06BAC4du2acL87Vj7c6Tot5WU6lVjN8GEwGHDo0CHcvHlT8WvYqnwsXrxYuM3Kh2ti+CDyMsbw4evrCx8fH8mKneILqF26dAkvvfSS5Be5UnJLdAOuHz7kKh8bNmxwQkvUFR8fL9l2ZPgIDQ0VFv26fv065s6di8TERDRp0sTidYdMyY35qFatmmxQZOXDNTF8EHkZ0ymI1pYL//rrrzF48GBs2bKlTMe4cuWK7P2uHj5MKx9Dhw5Fx44dndQa9ZhOVY2NjXXYsbRarbBa7LVr1/Dqq68CKL2WjtJBz3KVj4CAAMyaNctsX1Y+XBPDB5GXKUv4MPrxxx/LdIzMzEzZ+109fJhWPsqz9Lc7Mg0fjv7CNna9XLhwQXK/eKyGNXLhAwBee+01PP3005J9WflwTQwfRF7GdAqikut2bNy4sUzHsFT5KM8y5WoyDUfe8lezafhwNPG4DzHTMGKJ3IBTI9P3GMOHa2L4IPIyppUPJeHj8uXLwiXMlZCrfPj7+6Ndu3aKX8MZTJdR94bBpgBQpUoVPPHEEwCA2bNnO/x4xhlWppSGD7kxH0am4cNbAqS7Yfgg8jKm4aNq1aqSy9zfc889WLFiBebPn49HH30UAKDX68u0/Lpc+Hj++edRpUqVijRddZa6jzyNRqPBunXrkJmZiX//+98OP967775r1j0ClC98sPLhnrxzUjuRl7p27ZoQPoxrO2i1Wmzbtg1r166FRqNB9+7dERMTAwDYvHmz8NybN28q7jZJS0sTbo8ZMwb33XcfevXqZa/TcKgWLVrg4MGDALzriqgajUa1MS6hoaH44osvsHLlSsn9lrrrTJUlfLDy4ZoYPoi8RHp6Ovr27Stst2nTRrgdExODl156yew5xlkJAHDjxg3FUzBTU1MBlAab999/361WDv3hhx9w3333ISAgAKNHj3Z2czyWXHefeE0Ya1j5cH/sdiHyEsOHD8euXbuE7e7du9t8jviqt2VZBMo4a6FGjRpuFTwAICEhAVlZWUhNTVU0HobKR6PRYMaMGZIxG0pXPGXlw/0xfBB5iePHjwu3e/TogYceesjmc8ThIysrS9Fx7t69Kywy5sjFqhwpJCTE5ZeC9wRTpkxBbm4u2rdvD6D0vSNe/t8S8WwXWwNOWflwTQwfRF6isLBQuL1q1SphlUlrxN0uffr0kbyGJcYuF8B9wwepx9/fH5UrVxa2r127ZjPosvLh/hg+iLyE8Sqf9erVU/wcceUDAPbs2WPzOeJVKu+55x7FxyLvJQ4fvXv3RlRUFCZMmGBxf475cH8MH0Rewli1KMvaFaZ/NRoDjDX79u0Tbt9///2Kj0XeSxw+9u7dCwD48MMPLe5vLXw0aNAAYWFhwnbt2rXt1EqyJ852IfIS5QkfVatWlWzfuHHD5nPEF6dr1aqV4mOR9xKHDyWsLTJWqVIlHD16FN999x3q16+v+uqtpAzDB5EXMBgMQtWiLGtXiKfjAsrCh3GwaXBwsFl4IZJjqSvQ0qq61pZXB0rHGk2ZMsU+jSOHYLcLkRcQ/7IuS+VDo9FIFoJSEj7u3LkDwPUvIkeuIykpCZMnTza73/heMmWt24XcA8MHkRcQj9Uo6/VKxDNelKz1YVyGneGDlNLpdJg5c6bZNNucnBzZ/Rk+3B/DB5EXEE+RLeuS4aarnKampiI7O9vi/sbwYVy+nUipgIAADBkyRNi+deuW7H4MH+6P4YPIC4jDR0UqHz/++CPi4+NRt25d2bUYioqKhGOx8kHlIZ6poiR8mA44JfdQpvCxbNkydOnSBcOGDbPa95ucnIyePXuidevWePPNNyX9zUSkPnt1u+Tk5ECv1+PWrVvYsmWL2b7iPnpWPqg8xOt0WAoftgackutTHD5OnjyJJUuWYPny5ejbty/mzp0ru5/BYMDMmTMxatQobN26FZcuXZL9JUVE6qlIt0tQUJDsQk1yq52KwwcrH1QeSsIHu13cn+LwsXPnTiQlJSE8PBwdO3bE0aNHZfcrKCjAyJEj0aFDBwQHB6N58+ZW+4eJyPEq0u2i0WgwefJkswAi98VgHO8BMHxQ+YjDh9yVloGKVfLINSjuLLt69Sratm0LoPSXkU6nw927d81+IQUEBAgXCQJKFxwaP368xdctLCw0+wtKp9O57RvKOC/d0vx0T8BzdD/iWQS+vr7Q6/VlOseJEydi4sSJWLt2LZ566ikA/3TBiN2+fVu4XalSJaf9+3naz0+Op56jOLTeuHEDly9fRmxsrGQf41oyQGm3oDv/G3jaz1HJNaOAMoQPvV4veVMEBAQgNzfX6rr5W7Zsgb+/P5o3b25xn4ULF+Kbb76R3Ne7d2/06dNHadNcUlpamrOb4HA8R/chvthbQUGBcMl7oGznmJ+fL3me+HUA4Ny5c8JtvV5v9rjaPOXnZ42nnaNpN8qFCxcQExMjue/SpUvC7Tt37jj9fWYPnvJzjI+PV7Sf4vARHBws6c8tKCiARqOxuH9OTg4+/fRTzJo1y+rrDh06FP3795c2ys0rH2lpaYiNjVWcAN0Nz9H9XLx4UbhdpUoVxMXFlescTQeax8XFSbaPHz8u3I6OjjZ7XC2e9vOT46nnGBsbi+rVqyMzMxNAaXA2PUfjejOVK1d2++XTPfXnaIvi8JGQkIBjx46hQ4cOKCgoQEZGhtkVL40MBgNmzJiBp556CgkJCVZf18/Pz22DhjVardbj30g8R/chnh3g7+8vOaeynKN45sutW7fMnpeXlyfcDgkJcfq/naf8/KzxtHPUarX4/vvv0alTJwDAxo0bERgYKPlj1ximq1Wr5jHn7mk/R1sUh4927drhiy++QPPmzbFnzx4kJiZanF+9cOFC5OXl4fnnn7dbQ4mo/Coy20VMvAbD8uXLkZubKxn8l5GRIdzmVFsqL/G1Xn7//Xf8/vvvsvtVq1ZNrSaRnSkOH6GhoZg5cybmzJmD8PBwTJo0CZs3b8bRo0cxduxYyb7ff/89DAYDunbtCgDo1q0bRo0aZd+We6i5c+fiyJEjmDFjBqKiopzdHPIQ9podEBISItlev369xX3FQYWoLGrVqoXGjRsjOTnZ6n4MH+6rTEvDJSYmYtGiRcJ2586d0blzZ7P9tm3bVuGGeaPk5GS88sorAIArV65g1apVzm0QeYyKTLUV8/X1RaVKlSTdK3IaN26MJ554otzHIe+m1Wrx+++/Y8uWLcjIyECVKlWg1Wpx5swZyQXoGD7cF9eldSF//fWXcHv16tVObAl5Gnt1uwClFQ1x+OjWrRuWLVsm2ScoKMjqgHQiW8LCwvD0008jJSUFcXFx0Gq1uHr1qiR8WJtJSa7Ne0a3uKiSkhIMGzYMSUlJNv+aJCovey7KZDqDJSwsDMHBwZL/GDzIEapWrSrZZnXNfTF8ONm6devw7bffYt26dZJET2RP9up2AYBHHnlEss2VTElNxlVPn376adSoUcPJraHyYvhwooKCAvTr10/Y5jL05AjZ2dmYOnWqsF3RbpeHH35Yss1ZLaSmuXPn4sSJE1ixYoWzm0IVwDEfTvTtt9+yq4UcbtKkSbh27ZqwXdHKh+lfm6x8kJo0Go3N9aPI9Xld5SMtLQ1z5syRLDftLHPmzLH6uMFgUKkl5KkuX76MnTt3CtthYWGSay+VR2RkpGSblQ8iKiuvCx8DBgzA6NGj8dxzzzm7KahcubLVx8XX0SAqq1WrViE2NhYnT54U7rt8+bJZeCgr8SqnACsfRFR2Xhc+jH8F7tmzx+mVBfG1ch5//HGzx02vo0FUFtOnT5e8x9u0aWOXKoXpxSRZ+SCisvKq8CG+rDgA5ObmOqklpdLT0wGUTl0cPXq02eMMH1QWxcXFOHz4sHAdl8OHD0seN70seXmZTqNl5YOIysqrwsfVq1cl28arJjpDYWGh0J4aNWrI/vXI8EFl0bdvX9x3330YPnw48vLyzC5SlZOT45DjsvJBRGXlVeEjKytLsn3kyBGkpKTg4Ycfxosvvgi9Xo+7d++qMtZCfAEuS+HDeNloIlv0ej1+/vlnAMCiRYtw9OhR6PV6yT5PPfWUQ47tiVelJiLH8urw0bt3b9SuXRs7d+7EN998Ax8fH1SqVAmBgYEYMWKEQ8aEpKSkYODAgXjrrbeE+2rUqIFKlSqZ7cvKh3vYsWMHxo0b59QZVKZVPWMQMRo0aBD69+/vkGMXFRU55HWJyHN5zTofu3fvxvz58xXvP3/+fHTu3Bm9evWyaztGjx5tdt2WmJgYp3W7FBUV4cyZMwCAOnXqICAgwOHH9CRFRUXo2bMnrl+/joMHD+K3336z22vfvXsXP//8M1q1aoV77rkHer0e165dM1tiGoBZ8Jk1a5Zwe/v27WYLg1VUw4YNceLECQDmy60TEdniNZWPKVOmlPlibZs3b7Z7O+Ta4Kxul9zcXNStWxeNGzdG48aNERsbiytXrjj0mJ4mPT0d169fB1B6NWd7VgEmT56MgQMH4sEHH8TNmzfRs2dPVKtWDe+++67ZvtaqLk2bNrVbm4xWrlyJzp07Y8aMGWjYsKHdX5+IPJvXhA9rXn75ZTRr1gyjR4/GkSNHhPvFq0I6krMGnO7atQtpaWnCdnZ2Nn799VeHHtPTiP/9AODAgQN2e+3Zs2cDKP25RERECMF10qRJwj7Xr19HixYt8Mwzz8i+RocOHczW5bCHe+65B7/++iumTJli99cmIs/nNd0uL774orCWRocOHXDhwgX89NNPeOuttyR/GYqXO1frWis1atSQHbTn6PAhvtKpkel0ZLLu77//lmxv374dbdq0sctrh4SE4Pbt27KPTZw4EY888gguXryIv/76S/LYl19+iejoaAQEBNi9u4WIyB68JnyYrmjaunVr9O3b12y/SpUqISAgAPn5+dixYwcWLFiA559/3mzaYnkY118wFRMTI3sJckd3u4ivdGrE8KHctWvXMHLkSMl9b775JnQ6HV599VWzxbjKqmbNmsK4ClMffPABPvzwQ7MxSVOnTjVrExGRq2G3iwzxsufDhw/HypUrLe6r1+uRlpaGy5cvy86OEX/Bm85IAICWLVsiJCRE9rUdXfmQG5/A8KGcpcGl48ePx8CBA8v8ellZWZL3i6Wqh5HBYJCMITp8+DCmTZtW5uMSEamN4UOG6TVXxo4dK7vf4cOH0aBBA9SqVQs1a9ZEjx49UFJSIjy+ceNGREREoE2bNigsLJQsahYZGYmff/4ZW7dula16ABAGMjqKXOWD15NRzrhCrZyff/4ZycnJil/r+++/R1RUFPz9/REREYH7778fly5dsvk8cYCsXr264uMRETkTw4cM0/Dh5+eHAwcOoEGDBhgyZAgMBgMuX76M++67D+fOnRP2W7t2Lfz8/DBmzBjMnj0bTzzxBPLy8rB3715EREQgMTFR2Pf1119Hz549ERoaarEdjl6Bld0uFSMOB/3790dWVpZkmfx169Ypfq1ly5YJt2/evIn9+/eXqS0+Pj6oUqVKmZ5DROQsDB8yTMOHr68vhgwZgjNnzuC7775D586dUbNmTYvPX7VqFcaNGye5TzyQVavVol+/fmbPW7lyJRISEoTt7Oxs2UGh9sJul4oRh4+pU6eiatWqknFESioXRkePHrX42P3334+4uDj4+Pjg66+/xr59+8z2qVatGnx8fBQfj4jImRg+ZJgu4qTVaiUl9C1btkge7927t+xVaS15/fXXUbt2bbP7n3rqKZw4cUIyiNCR1Q9WPkr9+OOPGDBgAEaMGIFjx44pes7KlSsl1QpjGK1Ro4ZwX3p6OvR6PXbv3o1Lly5JuuRMiStgpt18UVFROH36NDIzM/Hiiy+iVatWCAsLk+wTHR2tqN1ERK7Aa2a7lEWXLl0wb948Ydt0OqWYRqPBK6+8gmrVquHy5cuIiYlB586dERISguDgYMybNw87d+5E7969MXjwYFSuXBmtW7e2enzTLzBHrSDJMR/A2bNn0bdvX+E6KMePH8euXbss7v/TTz9h1qxZ+PPPP4X7KleuLMxsEY+7SE9Px7fffosXX3xRuK9v375YsmSJ2Tgf4/ie2NhYtGrVSvJYSEgI/Pz8JN0qDRo0kHTNmD6HiMiVMXzI6N69O5o0aWL1r+DJkydj2LBh8PX1FcKC8WJeKSkpiIuLg1arRc+ePZGamoq6detaHFhqShw+3njjDcTExCAuLg5vvvmmXS9f7m3dLgaDAX/99RcSEhKERd1Wr14tuQDb2bNnLT4/Ly8Pzz33nNmU6REjRgi3jSEhOzsbGRkZkuABlI7tOH/+PBYuXIhGjRoJ7TKGj8jISNSpU0fyHLnZUE2aNJGEj5deesnquRMRuRKGDxk+Pj7YsmULmjRpIrvQ2JgxYzBz5kxFr+Xn54d69eqV6fgxMTHC7R07dgi3AwMD7bqipLd1u0yfPh3Tp09HYmIi9u/fD61Wa7ai661btyw+f/fu3WbB44cffjC7YFuNGjWQnZ2NlJQU2dfZt28f+vfvj0OHDuH69euYMGGC8LOIiIhAfHy8ZH+5wGk65qh58+YW201E5Go45sOCqKgonDhxwmxgaNu2bfHhhx869NjdunWTBBCjbdu22fU43tbtMn36dADAX3/9JVwL5fTp05J98vLyLC4Gt2nTJrP7nnzySbP7lIy/OHr0KD799FNUrlwZCxYsEO4PDw9HZGSkZF+dzvxvhE6dOgm3hw8fbvN4RESuhOHDiipVquCHH36QfJlMnDjR4bMKIiMjcfHiRZw7dw7nzp0T/srdv3+/1UGLZeVt3S5iZ8+eRXFxseyMFNPFvdLT09GyZUt88sknkvs//vhj2S6RatWq2Ty+Xq/HxIkTze7PzMyERqORVLjEM6CMHnzwQUyaNAn9+/fHBx98YPN4RESuhN0uNmg0GsybNw8ffPABBg4ciKSkJFWOq9PphL7/1q1b49KlS8jNzcW5c+fQoEEDuxzD27pdxE6dOoV69erJhrlbt25JZpMsWbIEBw8eFLabNWuG7777Ds2aNZN9bdOp2mI1a9YUAo/cNGpj5WnatGmIjIxETk6O7GUANBoN3n77bYvHISJyZQwfCvTo0QM9evRw2vHFs12uXLnC8FEOpkvfnzx5Eo0bN5bd13TcR1ZWlnDb398f69evl+0WMzINH9HR0cjIyMCDDz6IZ555Bv/6178kj7dv3x5//PEHioqKhIqHVqs124+IyFMwfLgB8ZfZtWvXhNsGgwF6vR5arVbxTBoxuW4XTx3zIV7kDShdfXTjxo3Cto+Pj1AFMe12EYeRP/74w2rwAGC20ujvv/+Oo0eP4vHHHzdbIwYA+vTpg88++wzXrl3Do48+quyEiIjcGMd8uAG58LFz505ER0dDp9OhWbNm5boOjDdVPj799FPJtnFMjZG4smVa+cjJyRFumy7uJce08lG7dm306NED/v7+aNu2rdlrtG/fHs2bN0fHjh3LFSKJiNwNw4cbkAsfn3/+Oa5cuQKgdBG0SZMmyV5V1xpx+DBO5/TE8FFSUoLJkydbfHzQoEFo166dsH3y5EnJ4+IwYu1aPEamlQ9xoIiIiMDs2bMljzdp0sTmaxIReRKGDzcgFz7OnDkj2eerr77CkiVLyvS64m6XiIgIAKXdE/acUeMKLl++LNlu3LgxfvjhB/zwww9Ys2YN5s+fLwkV//73vyXBrKKVD1ODBw/GI488AgCYOXMmqx1E5HU45sMNmIYPg8GA8+fPm+23YMECswWvrBF/wcbFxSEtLQ16vR6ZmZk2xzW4E9N/q5iYGLN/J+Py6EZpaWnC+hrG8BEYGAhfX1+bx7O1Cq2Pjw82bdqEzMxMqxcoJCLyVKx8uAFx+Pj222/x999/mw2KBEoXzyoLcfgQL+ldlquxurL8/HyMGjUKTz/9tOT+kSNHmu1rXOrc6ObNm8JtY7eLki4XoHSMR9OmTQEA77//vuw+fn5+qFWrFrRafgSJyPvwN58bMC3ji9eXGDJkiHD71q1buHHjhuLXFXe71K1bV7idlpZWjla6njlz5uDzzz+XBImkpCR0797dbN/mzZujVq1awrb439FY+VDS5QKUTpPdu3cvjhw5gvHjx5ez9UREnovhww0EBARYvGppt27dJH/JHzp0yOLrnDp1SnLFVnHlQ3w9EU+pfKxcuVKy7ePjgy+//FJ2hVqNRoNXX31V2D5z5gyuXbuGrKwsofKhNHwApV00TZs25XgOIiIZDB9uYvPmzcIgRaM33ngDvXr1wgMPPCDct2vXLhgMBpw6dUqyguaxY8eQmJiI9u3bY/DgwTh06JDQdaPT6SR/9Ve08pGenl7mmTf2duvWLcll7wcOHIhly5YhNjbW4nPCw8OF26+++ipatWqF6Oho4VyUdrsQEZF1DB9uIjw8HIsWLRL+an/yySfx7rvvQqPR4KGHHhL2mzZtGrRaLRISElC7dm1s27YNly5dQocOHYSFthYvXozExEQkJycDKB1/IB7zYTrVtCxee+01xMTEyC4JrqbLly8LoWHgwIFYvHgxnnnmGavPMc74scT0UvdERFQ+nO3iRmrVqoXFixdj586dmDZtmnB/XFwcEhISzEJDZmamohUz8/PzUbNmTYSFhSEnJwcbNmzAnDlz0KVLF9xzzz2K27d161Z88cUXAIAVK1Zg/vz5ZeqqsCfjGigAUL16dUXPEVc+AKBNmzaoXLkyNBoNoqOjMWnSJHs2kYjIazF8uJl+/fqhX79+kvs0Gg2+//57PP300zbHawwYMABVqlTB+vXrhbVC9Ho9NBoNGjZsiL179wIARo8ejdDQUPz2229o0aKForbt2LFDsn3kyBG0b99e6anZVWZmpnBbafgwrXx8/fXXaNy4MWekEBHZGX+reoiWLVvi4sWLVvd599138f333+OTTz7Bf//7X7PHTUPGrVu30LJlSyQlJeHo0aOy14IRO3v2rGTb2uBXeyoqKsKmTZskwUtc+YiKilL0OqaVD1vrdRARUfkwfHgQHx8fPPfcc8L2W2+9hS1btmDjxo3Yv38/Jk6cKDzWsmVLJCQkAIAwkHX06NFo0aIF2rZtK3nddevWoVmzZqhevTp+/fVXJCcnw2AwICsrC6+++iqSkpJw9uxZs/Dxxx9/OOpUJd5//3107doVrVq1EpaHL0/lwzR8EBGRY7DbxcN89NFHOHDgAMLCwjB27FiEhITI7qfRaLBp0yasWbMGvXr1AgDUr18fBw4cAABcuHDBbIDl9evX8fjjjwMAevXqhcLCQqxduxZAaUAxtXz5ctx7772YMGGCsFqoven1erz11lsASgPH4cOH0aZNm3JVPipXroy+ffti5cqVWLBggUPaS0REDB8eJyYmBqdOnVK0vkRcXBxee+012cfi4+MxYsQIfP3117KP//zzz4raM3nyZOj1eowdO9ZsCfOKOnjwIFq2bCm579SpU2jTpo1kSfXo6GjFr7l06VIUFBTA19cXKSkpdmsrERH9g90uHsheC1t9/vnnOHr0KAoKCrB48WJFz6levbrZrJC33noLtWvXFgaz2oPBYMArr7xidv/x48dRWFiIffv2ASgNWLYu9GbK39/fLm0kIiJ5DB9kka+vL+699174+fnh6aeftnixuUaNGuH1119HcnIyUlNT8fbbb+P69euoV6+esE9WVhaee+456PV6u7Tt9OnTkkXEjD777DMMGjRIGPvx4IMP2uV4RERkPwwfpEhwcDAOHjyIbdu2oVevXoiIiMA999yDH374AcnJyZg1axYaNWokXPU1IiICe/bskVzU7eLFiwgLC7NLBcS4QBoATJ06Fffeey+A0iXjly9fLjz22GOPVfhYRERkXxzzQYpFRUUhKioK7du3R0pKCuLi4qyugVG1alX88ssvWLp0qbA2SW5uLt544w1s27ZN2O/YsWPw8fFBw4YNFbfl+PHjwu3GjRujXr16GDhwoGSfNm3aYMCAAYpfk4iI1MHKBzlcr1690K1bN2H73Llzwu0///wT9957L5o2bYqdO3ciNTUVQ4YMkaxDsm3bNqxbt05yvRhx+GjUqBHuu+8+yTG7dOmCTZs2OWyWDRERlR/DBzmcn58f1q1bh6ZNmwIonRJrDBLGWTPFxcV4+OGHkZSUhO+++w4DBgxApUqV0L9/fzz66KNISkrC+vXrAZQuB79582bhtevXr4+6detKjjlz5kxeCI6IyEUxfJBqjFNei4qKcP36dQDA1atXJfscPXpUuH337l0sWbJE2DZeN2bdunW4du0agNKqip+fHwICAiSvY1xAjYiIXA/DB6lGvNJoeno6ANhcEl7MuLrqwYMHhfvEV881Ljb21FNPWVxcjYiInI8d4qQa8WJfzZs3R0lJCS5cuCC779SpU3Hp0iUcPXoU+/fvF+5/+eWXJcGiWbNmwu3p06dj2LBhqFmzpgNaT0RE9sLwQaqpWrWqcFuv1+N///ufsIpoixYt8O677+LSpUuoX78+HnroIWHfjRs34oknngAA7Nq1S7g/NDQUtWrVkhwjNjbWkadARER2wPBBqnn00Ucl2507dxZud+jQQbIt1rVrV8yePRtjxoyR3N+0aVO7reZKRETq4ZgPUk3z5s0lFQ0jnU6Hl156yepzTYMLADz88MN2axsREamnTOFj2bJl6NKlC4YNG4YbN25Y3O/q1at4/vnn0aVLF/z0008VbiR5jieffNLsvlWrVkmWYpfTpEkTs6mzHTt2tGvbiIhIHYrDx8mTJ7FkyRIsX74cffv2xdy5cy3u+/7776NDhw5Yt24d1q9fj8zMTLs0ltyfeMYLAJw5c0ayAJklPj4+mDBhgrCiaocOHWSrKERE5PoUh4+dO3ciKSkJ4eHh6Nixo2Q9BrGioiIcPHgQffv2ha+vL7p06YI9e/bYrcHk3qKioiTbderUUfzcN998Ezdv3kR2dja2bdvG1UuJiNyU4t/eV69eRdu2bQGUXrJdp9Ph7t27CAwMlOx38+ZNREdHw8/PD0DpX7pHjhyx+LqFhYUoLCyUNkqnE57vboxXbbXX1VtdUUXOUW79jbK8TlBQEIKCghz+78ufo3vz5HMz4jl6Bk87R2vX+xJTHD70ej2Cg4OF7YCAAOTm5pqFD9P9AgMDkZuba/F1Fy5ciG+++UZyX+/evdGnTx+lTXNJaWlpzm6Cw5XnHCMiIhAdHY2MjAxMnTpVmGrrqvhzdG+efG5GPEfP4CnnGB8fr2g/xeEjODgYd+7cEbYLCgpkpzkq3c9o6NCh6N+/v7RRbl75SEtLQ2xsrOIE6G4qeo7Hjh3DuXPncN9997nsvxF/ju7Nk8/NiOfoGbzhHOUoDh8JCQk4duwYOnTogIKCAmRkZCA8PNxsv6CgIBQXFyM3NxfBwcE4deoUqlWrZvF1/fz83DZoWKPVaj3+jVTec4yMjERkZKQDWmR//Dm6N08+NyOeo2fwhnMUU3ym7dq1w8aNG7F792589tlnSExMtDjgr2PHjvjggw/w559/4ueff0b79u3t1mAiIiJyb4rDR2hoKGbOnIkFCxYgPT0d48ePx+bNmzFr1iyzfYcOHYrQ0FDMnj0bw4cPR4MGDezaaCIiInJfZZqrmJiYiEWLFgnbnTt3ll0S28/PD+PGjatw44iIiMjzeE8HExEREbkEhg8iIiJSFcMHERERqYrhg4iIiFTF8EFERESqYvggIiIiVTF8EBERkaoYPoiIiEhVDB9ERESkKoYPIiIiUhXDBxEREalKYzAYDM5uBBEREXkPVj6IiIhIVQwfREREpCqGDyIiIlIVwwcRERGpiuGDiIiIVMXwQURERKpi+CAiIiJVMXwQERGRqhg+iIiISFUMHxXw2muvYcmSJc5uhsMlJSUhPT3d5j7u5r///S86deqEpKQk/Pnnn85ujl0YDAa89957aNeuHbp164a9e/cCAObMmYNOnTrh3//+N/Lz8wEAly5dQv/+/dG6dWuMHDkSubm5AIDk5GT07NkTrVu3xptvvoni4mKnnY8S3vI5BPhZdCf2+CwWFRXh888/x/DhwzFv3jyX/yyWBcNHORUXF+Pw4cM4ePCgs5tC5XD27FksWrQIP/zwAyZPnoy33nrL6gf7wIEDOHXqlIotLJ9ff/0VGRkZWL9+PUaPHo0PP/wQ27dvx4EDB7B27VokJiZi6dKlAID3338fPXv2xPbt2xEYGIgff/wRBoMBM2fOxKhRo7B161ZcunQJW7ZscfJZWcbPofvjZ1H+swgA//nPf1BQUIApU6YgOTkZ69evd+Yp2RXDRzkdP34c9913H06ePAm9Xu/s5lAZ7dmzBw888ACioqLQunVr6HQ6q7/QDh48iNOnT6vYwvKpXr06Jk+ejPDwcLRt2xbZ2dnYsWMH+vTpg4CAADz99NPYtWsXDAYDevTogV69eiEwMBCtWrXC1atXUVBQgJEjR6JDhw4IDg5G8+bNkZ2d7ezTsoifQ/fHz6L8ZxEAQkJC8Nprr6FWrVp46KGHcOnSJSeflf3onN0Ad3XgwAG0bNkSxcXFOH36NJYtW4aSkhL89ddfiIiIwDvvvIO4uDgcOHAA69atQ1xcHJYuXYoVK1YgPDzc2c0vs/nz56NFixZCSTcpKQlr1651cqvKLyMjA1FRUcJ21apVkZGRgXXr1uG3335DREQEpk+fjri4OPTo0QN5eXnQarX44osv8PHHH6NJkyZObL1lzZs3F27v378fTZo0QVZWFurVqwcACA4Oxs2bN6HRaNCpUydh33379uGxxx5DQEAA2rdvL9x/4MABjB8/XrX2l5W3fQ4Bfha95bMIAP369QMAoYIybtw49U7AwVj5KKeDBw/ivvvuw3333YcDBw4AAPLz87F27Vo89dRTmDVrlrDv3r17cf36dSxZsgRhYWHOajKJ5Ofnw9fXV9j29fXFxYsXceXKFaxfvx4vvPACZs+ejYCAAPz6668YMGAAxo4di19//dVlf9mJFRcX45tvvsGAAQNgMBgQHBwsPFZSUiLZ99ixYzhz5ozkFyAAbNmyBf7+/pJfoq6Gn0P3x8/iP+Q+i9nZ2Rg2bBj8/f2RkJCgWrsdjeGjHIqLi/H333/j9ddfx9KlS4Vfet27d4dWq0XXrl3x999/C/uHhoZizJgxqFKlCjQajbOardjFixeFczISt9tgMKjdJLsLCAhAYWGhsF1YWIivvvoKTz75JHQ6HTp16oSvv/7aiS2smB9++AExMTFo27YtgoKCcOfOHeEx8XkXFRXhnXfewbhx4yRfADk5Ofj0008xYcIEVdtdFp7+OQT4WeRnEahSpQrWrl2LmjVrYvHixaq23ZEYPsrh2LFjaNiwITZv3owNGzbg6NGjKCkpEX4RGAwGaLX//NM2atTIbX7ZAaUDwFauXClsFxYWStJ6VlaWM5plVzExMbhy5YqwffXqVbRo0ULYLikpwc8//+yMplXYsWPH8NNPP+HNN98EACQkJODYsWMAgMzMTPj7+wv7fvbZZ2jUqJGkq8VgMGDGjBl46qmnXPovLU//HAL8LALe/Vncvn07AECr1eLhhx/GxYsXVWu7ozF8lMOBAwfQqFEjAKWpPSoqCjk5OVi3bh30ej02bNiApk2bOrmV5Ve/fn0kJyfjzp07OHXqFCpVqoSoqCjhF8Ty5cud3MKKa9u2Lf744w9kZmZi79690Ov1eOSRR7Bu3ToUFxdj//79WLVqlbB/WFiYcP43b950TqMVuHnzJiZMmIC33noLERERAIDHHnsMixcvxv79+/HJJ5/g4YcfBgBs2rQJ+/btM+tHXrhwIfLy8vD888+r3v6y8PTPIcDPord/FpcsWYJNmzbBYDDgt99+Q+PGjVU/D0fhgNNy+Ouvv/D0008L240bN8bGjRvRuXNnJCUlITIyEu+++64TW1gxcXFx6NmzJ3r37o2AgABMmjQJsbGxGDNmDA4fPowHHnjA2U2ssDp16mDYsGEYOHAg/P39MWPGDCQmJuLixYvo3r07KleujKlTpwr7P/744xgzZgyWLl2Knj174pVXXnFi6y3buHEjsrOzMWXKFOG+ZcuWYdSoUfj0008RHx+P4cOHAwAWL16MzMxM9OjRAwDQsmVLvPPOO/j+++9hMBjQtWtXAEC3bt0watQo9U/GBk//HAL8LHr7Z/HNN9/EW2+9hU8++QQPPfQQnnnmGaeciyNoDJ7QaegCpk2bhu7du6Nly5bObgqR1+LnkMg9sNuFiIiIVMXKBxEREamKlQ8iIiJSFcMHERERqYrhg4iIiFTF8EFERESqYvggIiIiVTF8EJHdpKenc40NIrKJ4YOInOLFF19060vBE1H5MXwQERGRqhg+iKhCdu3ahaeeegodO3bE+vXrhfsPHz6Mfv36oV27dhg0aBDOnz8PAHj33XfRsmVL/PXXX5g+fTpatmwpuQZLcnIyBg8ejIcffhjjxo1Dbm6u6udERI7F8EFE5Xbt2jW88cYbGDx4MBYtWoRdu3YBAPR6PSZMmIBHH30Uq1evRmJiIj799FMAwJgxY7Bt2zY0a9YMEyZMwLZt2zBmzBgAwO3btzFq1Ci0bdsWy5Ytw507d/DJJ5846/SIyEEYPoio3P744w/UqFEDTz/9NGJjY/Hiiy8Kj/33v//FoEGDcOXKFdy+fRspKSkAgICAAISEhMDHx0e4HRAQAADYvXs3dDodXnzxRURHR2PAgAHYuXOnU86NiBxH5+wGEJH7ys7ORvXq1YXtmjVrAgC0Wi2WLFmC1atXIyYmBlFRUdDr9TZf78qVK7h58yYeeeQRAIDBYMCdO3dQUFAAf39/x5wEEamO4YOIyi0iIgLZ2dnCdmZmJgDgwIEDWL16NX788UdERkZi9+7dOHnypOS5Wq0Wpte1jIqKQkJCAt577z0ApeEjNzcXOh1/VRF5Ena7EFG5PfDAA7h48SLWrVuHS5cuYf78+QCAvLw8AKVjOA4fPoxPPvnELGjUrFkT+/fvR3Z2Nv7880+UlJTgwQcfRGZmJpKTk+Hv74+tW7di1KhRZs8lIvemMfBTTUQVsHXrVsyZMwf5+fl44okn8P3332Pv3r2YNm0aduzYgRo1aiApKQmff/45NmzYgMqVKwMAMjIyMGnSJBw/fhzVq1fHTz/9BJ1Oh+TkZHz44Yc4d+4c6tSpg/Hjx6NJkyZOPksisieGDyIiIlIVu12IiIhIVQwfREREpCqGDyIiIlIVwwcRERGpiuGDiIiIVMXwQURERKpi+CAiIiJVMXwQERGRqhg+iIiISFUMH0RERKSq/wObtWR+drbHxgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pred_air = model.predict(n=12,series=train_stock1, past_covariates=air_covs)\n",
    "print(\"model {} obtains MAPE: {:.2f}%\".format(model, mape(pred_air,val_stock1)))\n",
    "stock1.plot(label='actual')\n",
    "pred_air.plot(label='forecast')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c7f695c",
   "metadata": {},
   "source": [
    "时间协变量的使用\n",
    "\n",
    "- 月份应作为未来协变量使用，并采用周期性（正弦/余弦）编码。\n",
    "- 小时和星期几应作为未来协变量使用。\n",
    "- 绝对位置（序列中的时间步）应作为过去协变量使用。\n",
    "- 相对位置（相对于预测时间的位置）应作为未来协变量使用。\n",
    "- 年份的一个额外自定义函数应作为过去协变量使用。\n",
    "  \n",
    "所有上述协变量都应使用`Scaler`进行缩放，该`Scaler`将在调用模型的`fit()`函数时进行拟合，并随后用于转换协变量。这种方法确保了输入到模型中的协变量被标准化或归一化，有助于提高模型训练的稳定性和预测的准确性。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3921c301",
   "metadata": {},
   "outputs": [],
   "source": [
    "def extract_year(idx):\n",
    "    \"\"\"Extract the year each time index entry and normalized it.\"\"\"\n",
    "    return (idx.year - 1950) / 50\n",
    "\n",
    "\n",
    "encoders = {\n",
    "    \"cyclic\": {\"future\": [\"month\"]},\n",
    "    \"datetime_attribute\": {\"future\": [\"hour\", \"dayofweek\"]},\n",
    "    \"position\": {\"past\": [\"absolute\"], \"future\": [\"relative\"]},\n",
    "    \"custom\": {\"past\": [extract_year]},\n",
    "    \"transformer\": Scaler(),\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "0a8a710d",
   "metadata": {},
   "outputs": [],
   "source": [
    "encoders = {\"datetime_attribute\": {\"future\": [\"month\", \"year\",\"dayofweek\"]}, \"transformer\": Scaler()}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "d24aeef3",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Specified future encoders in `add_encoders` at model creation but model does not accept future covariates. future encoders will be ignored.\n",
      "GPU available: True (cuda), used: True\n",
      "TPU available: False, using: 0 TPU cores\n",
      "IPU available: False, using: 0 IPUs\n",
      "HPU available: False, using: 0 HPUs\n",
      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n",
      "\n",
      "  | Name          | Type             | Params\n",
      "---------------------------------------------------\n",
      "0 | criterion     | MSELoss          | 0     \n",
      "1 | train_metrics | MetricCollection | 0     \n",
      "2 | val_metrics   | MetricCollection | 0     \n",
      "3 | stacks        | ModuleList       | 6.2 M \n",
      "---------------------------------------------------\n",
      "6.2 M     Trainable params\n",
      "1.4 K     Non-trainable params\n",
      "6.2 M     Total params\n",
      "24.787    Total estimated model params size (MB)\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c0fe57c1d43545a1b955d5779fb58acf",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Training: |          | 0/? [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "`Trainer.fit` stopped: `max_epochs=50` reached.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "NBEATSModel(output_chunk_shift=0, generic_architecture=True, num_stacks=30, num_blocks=1, num_layers=4, layer_widths=256, expansion_coefficient_dim=5, trend_polynomial_degree=2, dropout=0.0, activation=ReLU, input_chunk_length=24, output_chunk_length=12, n_epochs=50, add_encoders={'datetime_attribute': {'future': ['month', 'year', 'week']}, 'transformer': Scaler}, random_state=0)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_stock1, val_stock1 = stock1[:650], stock1[650:]\n",
    "#train_stock2, val_stock2 = stock2[:650], stock2[650:]\n",
    "model = NBEATSModel(input_chunk_length=24, output_chunk_length=12, n_epochs=50,add_encoders=encoders,random_state=0)\n",
    "model.fit(train_stock1, verbose=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "8a0ad5d1",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GPU available: True (cuda), used: True\n",
      "TPU available: False, using: 0 TPU cores\n",
      "IPU available: False, using: 0 IPUs\n",
      "HPU available: False, using: 0 HPUs\n",
      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "80f45266e83542dfba2a194c12e5c03e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Predicting: |          | 0/? [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "probabilistic_forecast = model.predict(30,series=train_stock1)\n",
    "\n",
    "stock1.plot(label=\"actual\")\n",
    "probabilistic_forecast.plot(label=\"probabilistic forecast\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "44292462",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "61d21c33",
   "metadata": {},
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {
    "height": "calc(100% - 180px)",
    "left": "10px",
    "top": "150px",
    "width": "171.443px"
   },
   "toc_section_display": true,
   "toc_window_display": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
